• Journal of the Korean Data and Information Science Society
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• v.11 no.2
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• pp.335-345
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• 2000

Most context use the classical norms on function spaces as the error criteria. Since these norms are all based on the vertical distances between the curves, these can be quite inappropriate from a visual notion of distance. Visual errors in Marron and Tsybakov(1995) correspond more closely to "what the eye sees". Simulation is performed to compare the performance of the regression smoothers in view of MISE and the visual error. It shows that the visual error can be used as a possible candidate of error criteria in the kernel regression estimation.

• Convergence Security Journal
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• v.8 no.2
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• pp.7-13
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• 2008

In domestic and international, evaluation of product with Common Criteria(CC) for security product estimation is expanding standard of product estimation. This expansion is due to multi aspects of product versions. However, it is very difficult to approach the most suitable form of security estimation guide in the developer's perspective, because estimation basis presented to developers is indefinite. With this pending dilemma, we are presenting a composition product introduce definite security standard for information security products.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1807-1810
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• 2002

This paper presents a technique for avoid- ing indefiniteness in Maximum Likelihood (ML) criteria for Direction-of-Arrival (DOA) finding using a sensor ar- ray with arbitrary configuration. The ML criterion has singular points in the solution space where the criterion becomes indefinite. Solutions fly iterative techniques for ML bearing estimation may oscillate because of numerical instability which occurs due to the indefiniteness, when bearings more than one approach to the identical value. The oscillation makes the condition for terminating iterations complex. This paper proposes a technique for avoiding the indefiniteness in ML criteria.

• ETRI Journal
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• v.45 no.2
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• pp.226-239
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• 2023

Challenges in cognitive radio and tactical communications include recognizing anonymously received signals and estimating parameters in a blind or semi-blind manner. In this paper, we examine this issue for orthogonal frequency division multiplexing (OFDM) signaling. There are several parameters in OFDM signaling, and the blind receiver must extract and consider the synchronization issue. We assume that the blind receiver is aware of modulation type, OFDM, and not aware of chip duration and the length of cyclic prefix. First, we present new criteria based on kurtosis to estimate these parameters and compare their performance at different levels of additive white Gaussian noise with methods based on correlation, kurtosis, maximum likelihood, and matched filter. Then, we perform synchronization and estimate the start time based on these criteria and several new criteria in two steps: fine and coarse synchronization. Finally, in a more practical setup, we present the idea of jointly estimating the mentioned parameters and the signal start time as coarse synchronization. We compare different criteria and show that one of the proposed criteria has the highest efficiency.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.543-551
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• 2020

In this paper, we introduce a method to improve the accuracy of the length estimation of targets using a radar. The HRRP (High Resolution Range Profile) obtained from a received radar signal represents the one-dimensional scattering characteristics of a target, and peaks of the HRRP means the scattering centers that strongly scatter electromagnetic waves. By using the extracted scattering centers, the downrange length of the target, which is the length in the RLOS (Radar Line of Sight), can be estimated, and the real length of the target should be estimated considering the angle between the target and the RLOS. In order to improve the accuracy of the length estimation, parametric estimation methods, which extract scattering centers more exactly than the method using the HRRP, can be used. The parametric estimation method is applied after the number of scattering centers is determined, and is thus greatly affected by the accuracy of the number of scattering centers. In this paper, in order to improve the accuracy of target length estimation, the number of scattering centers is estimated by using AIC (Akaike Information Criteria), MDL (Minimum Descriptive Length), and GLE (Gerschgorin Likelihood Estimators), which are the source number estimation methods based on information theoretic criteria. Using the ESPRIT algorithm as a parameter estimation method, a length estimation simulation was performed for simple target CAD models, and the GLE method represented excellent performance in estimating the number of scattering centers and estimating the target length.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.85-95
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• 1995

The error intensity models for the ML estimation of a signal parameter have been developed in a companion paper [1]. While the methods described in [1] are applicable to any estimation problem with continuous parameters, our main application in this paper is the time delay estimation, and comparisons among the models derived in [1] (i.e. LC, LM, and ALM models)have been made. We first consider the case where only additive Gaussian noise is involved, and then the shot noise environment where coherent impulsive noise is also involved in addition to the Gaussian noise. We compare the models in terms of the probability of error, MSE(Mean Squared Error), and the computational complexity, which are the most important performance criteria in the analysis of parameter estimation. In conclusion, the ALM model turned out to be the most adequate model of all from the viewpoints of the criteria mentioned above.

• Journal for History of Mathematics
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• v.16 no.3
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• pp.95-100
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• 2003

The recent surge of interest in the more technical aspects of nonparametric density estimation and nonparametric regression estimation has brought the subject into public view. In this paper, we investigate the general concept of the nonparametric density estimation, the nonparametric regression estimation and its performance criteria.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.963-973
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• 2019

This study reviews a urban flooding risk criteria estimation model to predict risk criteria in areas where flood risk criteria are not precalculated by using watershed characteristic data and limit rainfall based on damage history. The risk criteria estimation model was designed using Support Vector Machine, one of the machine learning algorithms. The learning data consisted of regional limit rainfall and watershed characteristic. The learning data were applied to the SVM algorithm after normalization. We calculated the mean absolute error and standard deviation using Leave-One-Out and K-fold cross-validation algorithms and evaluated the performance of the model. In Leave-One-Out, models with small standard deviation were selected as the optimal model, and models with less folds were selected in the K-fold. The average accuracy of the selected models by rainfall duration is over 80%, suggesting that SVM can be used to estimate flooding risk criteria.

• Journal of Oral Medicine and Pain
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• v.10 no.1
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• pp.73-89
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• 1985

This study comprised 157 extracted teeth, 73 of the teeth originated from mates and 84 from females, the age range was 12-79 years. The correlation coefficient of each Gustafson's criteria in relation to age was carried out. Age estimation were performed on 157 teeth according to the method by Gustafson and by use of multiple regression, as used by Johanson, after evaluating the six criteria of Gustafson by multiple regression computer analysis. Two prediction formulas and standard deviations were compared with each other. The results were as follows : 1. The author found that six Gustafson's criteria had strong correlation with age except root resorption, and correlation coefficients were r = 0.79 (Transparent dentin), r=0.72 (Secondary dentin), r 0.69 (Periodontal change), r=0.63(Attrition), r = 0.39 (Root resorption), respecti vely. 2. The age estimation formula by Gustafson's method was calculated as follows: Y 8.88 + 3.52X r =0.87, r2 = 0.76, SD = 8.18, F = 483.56, P < 0.01 The age estimation formula by multiple regression was calculated as follows: Y 8.57 + 6.37T + 6.37T + 4.63P + 2.70S + 2.40C + 3.08A + 1.34R r= 0.89, r2 = 0.78, SD = 7.82, F = 91.62, P < 0.01, Durbin-Watson Coefficient = 1.09 3. In comparison of two estimation formulas, the formula by multiple regression, the method of Johanson, was found to be slightly more reliable than Gustafson's method. Gustafson's method SD = 8.18, Multiple regression (Johanson's method) SD = 7.82 4. It was reaffirmed that Gustafson's six criteria could be a independent variable in multiple regression analysis.

• International Journal of Contents
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• v.8 no.1
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• pp.39-46
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• 2012

Character segmentation is a preprocessing step in many offline handwriting recognition systems. In this paper, Chinese characters are categorized into seven different structures. In each structure, the character size with the range of variations is estimated considering typical handwritten samples. The component removal and merge criteria are presented to remove punctuation symbols or to merge small components which are part of a character. Finally, the criteria for segmenting the adjacent characters concerning each other or overlapped are proposed.