• 한국정보처리학회논문지
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• 제2권4호
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• pp.611-618
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• 1995

고도의 정보화 사회에서 데이터의 내용변경, 중요한 데이터의 불법적인 유출, 순 서 변경 그리고 미확인 송신자와 수신자등에 의하여 항상 위협을 받음으로써 데이터의 안전성이 요구되고 있다. 본 연구에서는 컴퓨터 통신의 안전을 위한 다변수 Knapsack 암호시스템을 제안하였다. 이 시스템은 기존의 Knapsack 암호시스템보다도 간단하면서 높은 안전성을 갖는다. 그리고 제안된 암호 시스템은 초증가벡터의 각 요소를 변형하 여 다변수 다항식으로 표현한 것을 암호벡터로 구성한다. 암호문의 복호는 비밀의 정 수와 초증가벡터를 사용하면 평문의 구해진다. 따라서 이 암호의 안전성은 비밀의 정 수를 다변수 다항식으로 나타내는 암호벡터에 대입할 때 암호벡터가 초증가벡터로 되 는 근을 구하는 것의 어려움에 근거하고 있다. 제안된 다변수 Knapsack 암호시스템의 타당성이 컴퓨터 시뮬레이션을 통하여 입증되었다.

• Journal of Information Processing Systems
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• 제10권3호
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• pp.395-411
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• 2014

Temporal medical data is often collected during patient treatments that require personal analysis. Each observation recorded in the temporal medical data is associated with measurements and time treatments. A major problem in the analysis of temporal medical data are the missing values that are caused, for example, by patients dropping out of a study before completion. Therefore, the imputation of missing data is an important step during pre-processing and can provide useful information before the data is mined. For each patient and each variable, this imputation replaces the missing data with a value drawn from an estimated distribution of that variable. In this paper, we propose a new method, called Newton's finite divided difference polynomial interpolation with condition order degree, for dealing with missing values in temporal medical data related to obesity. We compared the new imputation method with three existing subspace estimation techniques, including the k-nearest neighbor, local least squares, and natural cubic spline approaches. The performance of each approach was then evaluated by using the normalized root mean square error and the statistically significant test results. The experimental results have demonstrated that the proposed method provides the best fit with the smallest error and is more accurate than the other methods.

• 한국수학교육학회지시리즈E:수학교육논문집
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• 제30권4호
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• pp.469-497
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• 2016

본 연구에서는 추상대수학의 체, 벡터공간, 최소다항식 등의 개념을 중심으로 삼차방정식 해의 작도(불)가능성을 학습할 수 있는 학습 자료와 초등수학적 접근을 구현한 학습 자료를 각각 개발하였다. 그리고 개발된 자료들에 대해 타당성, 학습 가능성, 장점 및 단점을 실험적으로 확인하였다. 본 연구에서 개발된 자료들은 중등학교의 수학 우수학생들, 수학을 배우는 대학생들, 수학교사들에게 유익할 것으로 기대되며, 3대 작도불능문제의 해결, 다양한 3차방정식의 해의 작도(불)가능성을 학습하는데 활용될 수 있을 것으로 기대된다.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제24권3호
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• pp.243-291
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• 2020

In this paper, multi-block generalized backward differentiation methods for numerical solutions of ordinary differential and differential algebraic equations are introduced. This class of linear multi-block methods is implemented as multi-block boundary value methods (MB₂ VMs). The root distribution of the stability polynomial of the new class of methods are determined using the Wiener-Hopf factorization of a matrix polynomial for the purpose of their correct implementation. Numerical tests, showing the potential of such methods for output of multi-block of solutions of the ordinary differential equations in the new approach are also reported herein. The methods which output multi-block of solutions of the ordinary differential equations on application, are unlike the conventional linear multistep methods which output a solution at a point or the conventional boundary value methods and multi-block methods which output only a block of solutions per step. The MB₂ VMs introduced herein is a novel approach at developing very large scale integration methods (VLSIM) in the numerical solution of differential equations.

• 한국측량학회지
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• 제17권3호
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• pp.257-264
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• 1999

본 연구는 근거리 수치사진의 카메라 렌즈방사왜곡의 보정에 있어서, 기존 상용 소프트웨어의 최소제곱법에 의한 좌표변환방법인 기하보정툴을 사용하지 않고, 주변환식으로는 카메라 검정자료에서 제공되는 고차다항식을, 역변환에 있어서는 Newton-Raphson의 비선형 방정식의근의 해법을 직접 사용하여 렌즈방사왜곡을 보정함으로써 기하학적 정확도가 최소제곱법에 의한 좌표변환방법에 비하여 약 0.04∼0.08화소 향상된 수치 사진화상을 얻을 수 있었다. 또한 기존 소프트웨어에 있어서는 고차다항식의 최소제곱법 적용을 위해서 동일한 경중률의 많은 기준점의 선정작업을 필요로 하나, 본 연구에서 제시한 기법은 이 작업이 필요 없으므로 작업의 효율성을 높일 수 있었다.

• 한국멀티미디어학회논문지
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• 제25권2호
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• pp.440-449
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• 2022

In recent years, the air pollution and Air Quality Index (AQI) has been a pivotal point for researchers due to its effect on human health. Various research has been done in predicting the AQI but most of these studies, either lack dense temporal data or cover one or two air pollutant elements. In this paper, a hybrid Convolutional Neural approach integrated with recurrent neural network architecture (CNN-LSTM), is presented to find air pollution inference using a multivariate air pollutant elements dataset. The aim of this research is to design a robust and real-time air pollutant forecasting system by exploiting a neural network. The proposed approach is implemented on a 24-month dataset from Seoul, Republic of Korea. The predicted results are cross-validated with the real dataset and compared with the state-of-the-art techniques to evaluate its robustness and performance. The proposed model outperforms SVM, SVM-Polynomial, ANN, and RF models with 60.17%, 68.99%, 14.6%, and 6.29%, respectively. The model performs SVM and SVM-Polynomial in predicting O3 by 78.04% and 83.79%, respectively. Overall performance of the model is measured in terms of Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and the Root Mean Square Error (RMSE).

• Geomechanics and Engineering
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• 제30권6호
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• pp.551-564
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• 2022

Fragmenting the rock mass is considered as the most important work in open-pit mines. Ground vibration is the most hazardous issue of blasting which can cause critical damage to the surrounding structures. This paper focuses on developing an explicit model to predict the ground vibration through an multi objective evolutionary polynomial regression (MOGA-EPR). To this end, a database including 79 sets of data related to a quarry site in Malaysia were used. In addition, a gene expression programming (GEP) model and several empirical equations were employed to predict ground vibration, and their performances were then compared with the MOGA-EPR model using the mean absolute error (MAE), root mean square error (RMSE), mean (𝜇), standard deviation of the mean (𝜎), coefficient of determination (R²) and a20-index. Comparing the results, it was found that the MOGA-EPR model predicted the ground vibration more precisely than the GEP model and the empirical equations, where the MOGA-EPR scored lower MAE and RMSE, 𝜇 and 𝜎 closer to the optimum value, and higher R² and a20-index. Accordingly, the proposed MOGA-EPR model can be introduced as a useful method to predict ground vibration and has the capacity to be generalized to predict other blasting effects.

• 제어로봇시스템학회논문지
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• 제10권3호
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• pp.205-215
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• 2004

The characteristic ratio assignment (CRA) method〔1〕 is new polynomial approach which allows to directly address the transient responses such as overshoot and speed of response time in time domain specifications. The method is based on the relationships between time response and characteristic ratios($\alpha_i$ ) and generalized time constant (T), which are defined in terms of coefficients of characteristic polynomial. However, even though the CRA can apply to developing a linear controller that meets good transient responses, there are still some fundamental questions to be explored. For the purpose of this, we have analyzed several sensitivities of a linear system with respect to the changes of coefficients itself and $\alpha_i$ of denominator polynomial. They are (i) the unnormalized root sensitivity : to determine how the poles change as $\alpha_i$ changes, and (ii) the function sensitivity to determine the sensitivity of step response to the change of o, and to analyze the sensitivity of frequency response as o, changes. As an other important result, it is shown that, under any fixed T and coefficient of the lowest order of s in denominator, the step response is dominantly affected merely by $\alpha_1, alpha_2 and alpha_3$ regardless of the order of denominator higher than 4. This means that the rest of the$\alpha_i$ s have little effect on the step response. These results provide some useful insight and background theory when we select $\alpha_i$ and T to compose a reference model, and in particular when we design a low order controllers such as PID controller.

• 대한치과교정학회지
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• 제48권4호
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• pp.236-244
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• 2018

Objective: The aim of this study is to compare the adaptation of a straight wire between brackets positioned at the mid-lingual surface and those placed gingivally by using a three-dimensional simulation software. Methods: This cross-sectional study was performed using OrthoAid, an in-house software. The subjects were 36 adolescents with normal Class I occlusion. For each dental cast, two bracket positioning approaches, namely the middle and gingival, were examined. In the middle group, the reference points were placed on the mid-lingual surface of each tooth, while in the gingival group, the reference points were positioned lingually on the anterior teeth. A 4th degree polynomial was adopted, and the in-plane and off-plane root mean squares (RMSs) of the distances between the reference points and the fitted polynomial curve were calculated using the software. Statistical analysis was performed using the paired-samples t-test (${\alpha}=0.05$). Results: The mean in-plane RMS of the polynomial curve to the bracket distance in the gingival group was significantly lower than that in the middle group (p < 0.001). The off-plane RMS was higher in the gingivally positioned brackets in the maxilla than in the middle group (p < 0.001). However, the off-plane RMS in mandible was not statistically significantly different between the two groups (p = 0.274). Conclusions: The results demonstrated that the gingival placement of lingual brackets on the anterior teeth could decrease the distance between a tooth and the straight wire.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1041-1041
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• 2001

Removal of variability in spectra data before the application of chemometric modeling will generally result in simpler (and presumably more robust) models. Particularly for sparsely sampled data, such as typically encountered in diode array instruments, the use of Savitzky-Golay (S-G) derivatives offers an effective method to remove effects of shifting baselines and sloping or curving apparent baselines often observed with scattering samples. The application of these convolution functions is equivalent to fitting a selected polynomial to a number of points in the spectrum, usually 5 to 25 points. The value of the polynomial evaluated at its mid-point, or its derivative, is taken as the (smoothed) spectrum or its derivative at the mid-point of the wavelength window. The process is continued for successive windows along the spectrum. The original paper, published in 1964 [1] presented these convolution functions as integers to be used as multipliers for the spectral values at equal intervals in the window, with a normalization integer to divide the sum of the products, to determine the result for each point. Steinier et al. [2] published corrections to errors in the original presentation [1], and a vector formulation for obtaining the coefficients. The actual selection of the degree of polynomial and number of points in the window determines whether closely situated bands and shoulders are resolved in the derivatives. Furthermore, the actual noise reduction in the derivatives may be estimated from the square root of the sums of the coefficients, divided by the NORM value. A simple technique to evaluate the actual convolution factors employed in the calculation by the software will be presented. It has been found that some software packages do not properly account for the sampling interval of the spectral data (Equation Ⅶ in [1]). While this is not a problem in the construction and implementation of chemometric models, it may be noticed in comparing models at differing spectral resolutions. Also, the effects on parameters of PLS models of choosing various polynomials and numbers of points in the window will be presented.