• Journal of applied mathematics & informatics
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• v.39 no.1_2
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• pp.93-103
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• 2021

In this paper I am considering several cryptological threads. The problem of the RSA cipher, like the Diffie-Hellman protocol, is the use of finite sets. In this paper, I generalize the RSA cipher and DH protocol for infinite sets using monoids. In monoids we can not find the inverse, which makes it difficult. In the second part of the paper I show the applications in cryptology of polynomial composites and monoid domains. These are less known structures. In this work, I show different ways of encrypting messages based on infinite sets.

• Journal of the Korean Society of Radiology
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• v.81 no.3
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• pp.632-643
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• 2020

Purpose To investigate the correlation between magnetic resonance (MR) image-based radiomics features and the genomic features of breast cancer by focusing on biomolecular intrinsic subtypes and gene expression profiles based on risk scores. Materials and Methods We used the publicly available datasets from the Cancer Genome Atlas and the Cancer Imaging Archive to extract the radiomics features of 122 breast cancers on MR images. Furthermore, PAM50 intrinsic subtypes were classified and their risk scores were determined from gene expression profiles. The relationship between radiomics features and biomolecular characteristics was analyzed. A penalized generalized regression analysis was performed to build prediction models. Results The PAM50 subtype demonstrated a statistically significant association with the maximum 2D diameter (p = 0.0189), degree of correlation (p = 0.0386), and inverse difference moment normalized (p = 0.0337). Among risk score systems, GGI and GENE70 shared 8 correlated radiomic features (p = 0.0008-0.0492) that were statistically significant. Although the maximum 2D diameter was most significantly correlated to both score systems (p = 0.0139, and p = 0.0008), the overall degree of correlation of the prediction models was weak with the highest correlation coefficient of GENE70 being 0.2171. Conclusion Maximum 2D diameter, degree of correlation, and inverse difference moment normalized demonstrated significant relationships with the PAM50 intrinsic subtypes along with gene expression profile-based risk scores such as GENE70, despite weak correlations.

• Journal of Korean Society of Steel Construction
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• v.11 no.1 s.38
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• pp.69-78
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• 1999

When the lateral forces are applied to a frame, columns in the frame are usually accompanied with sidesway. If this sidesway is large, the frame is subjected to buckling and an early yielding of members which reduces the overall frame stiffness. In this study, numerical analysis of frames were conducted to evaluate the ultimate lateral strength of steel moment resisting frames permitted to sidesway under axial and lateral forces, and develope the procedure for determining the limits of column slenderness ratios. In the numerical analysis, the effects of the relative stiffness ratio between beam and column, deterioration of overall frame stiffness, slenderness ratio and loading conditions were considered. The elasto-plastic analysis method in which the $P-{\Delta}$effect is implemented, presented by the author previously, was adopted in the analysis. Incremental lateral forces were applied to the frame under constant axial loads and the generalized inverse is employed for the post-ultimate behavior.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.697-710
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• 2021

Relative error prediction is preferred over ordinary prediction methods when relative/percentile errors are regarded as important, especially in econometrics, software engineering and government official statistics. The relative error prediction techniques have been developed in linear/nonlinear regression, nonparametric regression using kernel regression smoother, and stationary time series models. However, random effect models have not been used in relative error prediction. The purpose of this article is to extend relative error prediction to some of generalized linear mixed model (GLMM) with panel data, which is the random effect models based on gamma, lognormal, or inverse gaussian distribution. For better understanding, the real auto insurance data is used to predict the claim size, and the best predictor and the best relative error predictor are comparatively illustrated.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.30-40
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• 2014

As the Hadamard transform can be generalized into the Jacket transform, in this paper, we generalize the Haar transform into the Jacket-Haar transform. The entries of the Jacket-Haar transform are 0 and ${\pm}2^k$. Compared with the original Haar transform, the basis of the Jacket-Haar transform is general and more suitable for signal processing. As an application, we present the DCT-II(discrete cosine transform-II) based on $2{\times}2$ Hadamard matrix and HWT(Haar Wavelete transform) based on $2{\times}2$ Haar matrix, analysis the performances of them and estimate them via the Lenna image simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.9
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• pp.869-876
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• 2017

Analysis of actuating forces and joint reaction forces are essential to determine the capacity of actuators, to control the mechanical system and to design its components. This paper presents an algorithm that calculates actuating forces(or torques), depending on the various types of driving constraints, in order to produce a given system motion in the joint coordinate space. The joint coordinates are used as the generalized coordinates of a kinematic system. System equations of motion and constraint acceleration equations are transformed from the Cartesian coordinate space to the joint coordinate space using the velocity transformation method. A numerical example is carried out to verify the algorithm proposed.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.11
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• pp.32-41
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• 1990

This paper proposes a method of using image features in serving a robot manipulator. Specifically, the con-cept 'feature' is first mathematically defined and then differential relationship between the robot motion and feature vector is derived in terms of Feature Jacobian Matrix and its generalized inverse. Also, by using more features than the number of DOFs of the robot, the visual servoing performance is shown to be improv-ed. Via various examples, the method of feature-based servoing of a robot proposed in this paper is proved to be effective for conducting object-oriented robotic tasks.

• Journal of the Chungcheong Mathematical Society
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• v.23 no.4
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• pp.679-689
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• 2010

By developing and using certain operators like those initiated by Burchnall-Chaundy, the authors aim at investigating several decomposition formulas associated with the $Kamp{\acute{e}}$ de $F{\acute{e}}riet$ function $F_{2:0;0}^{0:3;3}$ [x, y]. For this purpose, many operator identities involving inverse pairs of symbolic operators are constructed. By employing their decomposition formulas, they also present a new group of integral representations of Eulerian type for the $Kamp{\acute{e}}$ de $F{\acute{e}}riet$ function $F_{2:0;0}^{0:3;3}$ [x, y], some of which include several hypergeometric functions such as $_2F_1$, $_3F_2$, an Appell function $F_3$, and the $Kamp{\acute{e}}$ de $F{\acute{e}}riet$ functions $F_{2:0;0}^{0:3;3}$ and $F_{1:0;1}^{0:2;3}$.

• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.37-48
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• 1995

This paper presents an sstimation of ARMA coefficients of noisy ARMA system using generalized total least square (GTLS) method. GTLS problem for ARMA system is defined as minimizing the errors between the noisy output vectors and estimated noisy-free output. The GTLS problem is solved in closed form by eigen-problem and the perturbation analysis of GTLS is presented. Also its recursive solution (recursive GTLS) is proposed using the power method and the covariance formula of the projected output error vector into the input vector space. The simulation results show that GTLS ARMA coefficients estimator is an unbiased estimator and that recursive GTLS achieves fast convergence.

• Journal of Power Electronics
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• v.17 no.1
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• pp.262-271
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• 2017

This paper studies the performances of five typical Phase-locked Loops (PLLs) for distorted and unbalanced grid, which are the Decoupled Double Synchronous Reference Frame PLL (DDSRF-PLL), Double Second-Order Generalized Integrator PLL (DSOGI-PLL), Double Second-Order Generalized Integrator Frequency-Lock Loop (DSOGI-FLL), Double Inverse Park Transformation PLL (DIPT-PLL) and Complex Coefficient Filter based PLL (CCF-PLL). Firstly, the principles of each method are meticulously analyzed and their unified small-signal models are proposed to reveal their interior relations and design control parameters. Then the performances are compared by simulations and experiments to investigate their dynamic and steady-state performances under the conditions of a grid voltage with a negative sequence component, a voltage drop and a frequency step. Finally, the merits and drawbacks of each PLL are given. The compared results provide a guide for the application of current control, low voltage ride through (LVRT), and unintentional islanding detection.