• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.5
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• pp.7-14
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• 1998

In this paper, Fractal analysis applied to evaluate machined surface profile. The spectrum method was used to calculate fractal dimension of generated surface profiles by Weierstrass-Mandelbrot fractal function. To avoid estimation errors by low frequency characteristics of FFT, the Maximum Entropy Method (MEM) was examined. We suggest a new criterion to define the MEM order m. MEM power spectrum with our criterion is proved to be advantageous by the comparison with the experimental results.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.414-417
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• 2007

In this paper we present an adaptive method for accelerating conventional Maximum Entropy Method (MEM) for restoration of Passive Millimeter-Wave (PMMW) image from its blurred and noisy version. MEM is nonlinear and its convergence is very slow. We present a new method to accelerate the MEM by using an exponent on the correction ratio. In this method the exponent is computed adaptively in each iteration, using first-order derivatives of deblurred image in previous two iterations. Using this exponent the accelerated MEM emphasizes speed at the beginning stages and stability at later stages. In accelerated MEM the non-negativity is automatically ensured and also conservation of flux without additional computation. Simulation study shows that the accelerated MEM gives better results in terms of RMSE, SNR, moreover, it takes only about 46% lesser iterations than conventional MEM. This is also confirmed by applying this algorithm on actual PMMW image captured by 94 GHz mechanically scanned radiometer.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.435-440
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• 2006

In order to understand changes of water temperature for thermal discharge of Hadong power plant in Gwangyang and Jinju Bay, it was analyzed for temperature data of representative season by MEM(Maximum entropy method) that is one of the spectral analysises. And due to understand effect of thermal discharge at each point, analyzed spectral data showed reactive energy rate of reference point by calculating energy from 24 time period to height frequency zone. As a result of spectral analysis, it showed that there were 9 points which are largely effected, 7 points which will be estimated, 6 points which is difficult to estimate, 14 points which rarely effected by thermal discharge.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.2 no.3
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• pp.119-127
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• 1990

Wave directional spectrum estimation methods for irregular waves were considered in this study. Until now, the Longuet-Higgins Method (LHM) initiated by Longuet-Higgins et al. (1963) has been widely used, but resolutions of the estimation were found to be low. Kobune's Maximum Entropy Method (MEM) for the estimation of wave directional spectrum, bas-ed on the entropy Principle showed higher resolutions comparing with the LHM . If the wave directional spectrum is of Delta functions, the MEM is exact in its estimation. It was also found that for a unimodal spectrum, if the Mitsuyasu's spreading coefficient is above 5, the estimation resolutions were high. In bimodal spectrum, as the angle difference between the two peaks increased, the resolution improved. The energy seems to transfer to the smoother peak in the smoothing of peak's peakedness. LHM has a tendency to estimate bimodal spectrum as a unimodal spectrum ； thus, except for its computational speed, the resolution of LHM falls far below that of MEM.

• Computational Structural Engineering
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• v.10 no.4
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• pp.185-193
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• 1997

A major problem of frequency analysis in the field of low-frequencies such as building or construction vibration is the way of signal processing which is appropriate to obtain included frequency content from the finite process to be measured. Therefore, it is the aim of the investigation reported herein to develop the signal processing algorithm which is analyzed without losing the reliability of the measurements in low-frequency domain. To accomplish the research objective, it was analyzed the problems on the way of signal processing in low-frequency domain, and compared the response characteristics of FFT with those of MEM (Maximum Entropy Method) about the low-frequency of vibration. This evaluation of the response characteristics is used in determining appropriate signal processing algorithm into the low-frequency domain.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1998.06b
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• pp.270-275
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• 1998

It was assumed that the voice of cattle is generated with the virtual white noise through the digital filter called the linear prediction filter, and filter parameters (prediction coefficients) were estimated by the maximum entropy method (MEM) , using the sound signal of the animal . The feature planes were defined by the pairs of two parameters selected appropriately from these parameters. The cattle voices were divided into three levels, that is the high, medium and low levels according to their total power equivalent to the variances of the sound signal . It was found that the straight lines could be used for recognizing tow cow and one calf for high level voices. For high and medium level voices, however, it was difficult or impossible to recognize individual cattle on the parameters planes.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.11a
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• pp.237-238
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• 2006

The electrical properties such as dielectric constants and dielectric losses in the spinel samples of $LiGaTiO_4$, Li(Ga,Eu)$TiO_4$, $Li(Ga.Yb)TiO_4$ have been characterized by varying measuring temperature and frequency. The long range order structures are analyzed by rietveld refinement method. and local atomic disorder structures are analyzed by MEM (maximum entropy method). The relation between the crystal structure and dielectric properties are discussed. $LiGaTiO_4$ spinel has the IMMA with lattice constant, a = 5.86333, b=17.5872. c = 8.28375 ${\AA}$, Li-sites are partially substituted by Ga or Ti. Two crystallographic oxygen sites are partially occupied(40~50%). The dielectric constants of $LiGaTiO_4$, $LiYbTiO_4$, and $LiGa_{2/6}Eu_{1/6}Ti_{1.5}O_4$ ceramics were 127, 75 and 272, respectively at 100 kHz. The dielectric relaxation were observed in the $LiGaTiO_3$ ceramics and the temperature where dielectric loss shows maximum was $390^{\circ}C$ at 1 kHz and increased with increasing the measuring frequency.

• Journal of Computing Science and Engineering
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• v.5 no.4
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• pp.288-293
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• 2011

To resolve ambiguities in speech act classification, various machine learning models have been proposed over the past 10 years. In this paper, we review these machine learning models and present the results of experimental comparison of three representative models, namely the decision tree, the support vector machine (SVM), and the maximum entropy model (MEM). In experiments with a goal-oriented dialogue corpus in the schedule management domain, we found that the MEM has lighter hardware requirements, whereas the SVM has better performance characteristics.

• Journal of The Korean Astronomical Society
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• v.38 no.4
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• pp.445-462
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• 2005

In a companion paper, we have presented so-called Spatio-Spectral Maximum Entropy Method (SSMEM) particularly designed for Fourier-Transform imaging over a wide spectral range. The SSMEM allows simultaneous acquisition of both spectral and spatial information and we consider it most suitable for imaging spectroscopy of solar microwave emission. In this paper, we run the SSMEM for a realistic model of solar microwave radiation and a model array resembling the Owens Valley Solar Array in order to identify and resolve possible issues in the application of the SSMEM to solar microwave imaging spectroscopy. We mainly concern ourselves with issues as to how the frequency dependent noise in the data and frequency-dependent variations of source size and background flux will affect the result of imaging spectroscopy under the SSMEM. We also test the capability of the SSMEM against other conventional techniques, CLEAN and MEM.

• Journal of Korea Water Resources Association
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• v.51 no.5
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• pp.439-449
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• 2018

Many potential sources of bias are used in several steps of the radar-rainfall estimation process because the hydrological and meteorological radars measure the rainfall amount indirectly. Previous studies on radar-rainfall uncertainties were performed to reduce the uncertainty of each step by using bias correction methods in the quantitative radar-rainfall estimation process. However, these studies do not provide comprehensive uncertainty for the entire process and the relative ratios of uncertainty between each step. Consequently, in this study, a suitable approach is proposed that can quantify the uncertainties at each step of the quantitative radar-rainfall estimation process and show the uncertainty propagation through the entire process. First, it is proposed that, in the suitable approach, the new concept can present the initial and final uncertainties, variation of the uncertainty as well as the relative ratio of uncertainty at each step. Second, the Maximum Entropy Method (MEM) and Uncertainty Delta Method (UDM) were applied to quantify the uncertainty and analyze the uncertainty propagation for the entire process. Third, for the uncertainty quantification of radar-rainfall estimation at each step, two quality control algorithms, two radar-rainfall estimation relations, and two bias correction methods as post-processing through the radar-rainfall estimation process in 18 rainfall cases in 2012. For the proposed approach, in the MEM results, the final uncertainty (from post-processing bias correction method step: ME = 3.81) was smaller than the initial uncertainty (from quality control step: ME = 4.28) and, in the UDM results, the initial uncertainty (UDM = 5.33) was greater than the final uncertainty (UDM = 4.75). However uncertainty of the radar-rainfall estimation step was greater because of the use of an unsuitable relation. Furthermore, it was also determined in this study that selecting the appropriate method for each stage would gradually reduce the uncertainty at each step. Therefore, the results indicate that this new approach can significantly quantify uncertainty in the radar-rainfall estimation process and contribute to more accurate estimates of radar rainfall.