• Communications for Statistical Applications and Methods
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• 제16권4호
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• pp.587-594
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• 2009

이 논문에서는 선형회귀모형의 오차항에 대한 변화점 검정 문제를 다룬다. 고정 혹은 변동 모형의 독립 변수와 약한 종속성을 가지는 오차항을 가정하는 관계로 통상적인 중회귀모형뿐만 아니라 ARMA 등의 시계열 모형까지 본 논문에서 포괄한다고 하겠다. 오차항의 분포 변화를 검정하기 위하여 회귀모형의 잔차에 기초한 확률밀도함수 추정값을 이용한다. 적절한 가정하에서 잔차를 이용한 검정이 실제 오차를 이용한 경우와 동일한 극한 분포를 가짐을 보였다.

• 한국정밀공학회지
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• 제16권3호통권96호
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• pp.215-221
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• 1999

The object of the thermal error compensation system in machine tools is improving the accuracy of a machine tool through real time error compensation. The accuracy of the machine tool totally depends on the accuracy of thermal error model. A thermal error model can be obtained by appropriate combination of temperature variables. The proposed method for optimal variable selection in the thermal error model is based on correlation grouping and successive regression analysis. Collinearity matter is improved with the correlation grouping and the judgment function which minimizes residual mean square is used. The linear model is more robust against measurement noises than an engineering judgement model that includes the higher order terms of variables. The proposed method is more effective for the applications in real time error compensation because of the reduction in computational time, sufficient model accuracy, and the robustness.

• 대한수학회지
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• 제45권6호
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• pp.1753-1767
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• 2008

Consider the nonparametric regression model $Y_{ni}\;=\;g(x_{ni})+{\epsilon}_{ni}$ ($1\;{\leq}\;i\;{\leq}\;n$), where g($\cdot$) is an unknown regression function, $x_{ni}$ are known fixed design points, and the correlated errors {${\epsilon}_{ni}$, $1\;{\leq}\;i\;{\leq}\;n$} have the same distribution as {$V_i$, $1\;{\leq}\;i\;{\leq}\;n$}, here $V_t\;=\;{\sum}^{\infty}_{j=-{\infty}}\;{\psi}_je_{t-j}$ with ${\sum}^{\infty}_{j=-{\infty}}\;|{\psi}_j|$ < $\infty$ and {$e_t$} are negatively associated random variables. Under appropriate conditions, we derive a Berry-Esseen type bound for the estimator of g($\cdot$). As corollary, by choice of the weights, the Berry-Esseen type bound can attain O($n^{-1/4}({\log}\;n)^{3/4}$).

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1998년도 봄 학술발표회 논문집(I)
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• pp.347-352
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• 1998

The purpose of this paper is to present and establish a procedure to predict the prestress forces during the service life of the structure. The statistical approach of this procedure is using the in-situ measurement data of the post-tensioning system to develop a nonlinear regression analysis. The method of least squares is used to fit a certain function a set of data. Use of a nonlinear model is achieved by its logarithmic transformation and sunsequent use of linear-regression theory. The regression analysis result can be used to check the prestress force during the service life so that the remaining prestress force is equal to or exceeds the design requirement. Results from the measurement data of PSC box girder bridge structure were used to demonstrate the procedures.

• 품질경영학회지
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• 제21권2호
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• pp.140-155
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• 1993

The characteristics of $I_{\lambda}$-optimality, one of the linear criteria suggested by Fedorov (1972) are investigated with respect to the D-and heteroscedastic G-optimality in case of non-constant variance function. Though having limited results obtained from simple models, we may conclude that $I_{\lambda}$-optimality is sometimes preferred to the heteroscedastic G-optimality suggested newly bv Wong and Cook (1992) in the sense that the experimenter's belief in weighting function exists in $I_{\lambda}$-optimality criterion, not to mention its computational simplicity.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.270-272
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• 2006

In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs) using symbolic coding for non-linear data. One of the major subject of genetic algorithms is representation of chromosomes. The proposed model optimized by the means genetic algorithms which used symbolic code to represent chromosomes. The proposed gFPNN used a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. The performance of the proposed model is quantified through experimentation that exploits standard data already used in fuzzy modeling. These results reveal superiority of the proposed networks over the existing fuzzy and neural models.

• 한국치위생학회지
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• 제19권3호
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• pp.351-362
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• 2019

Objectives: The study aimed to analyze the factors affecting the maturity of dental biofilm, which was assessed with quantitative light-induced fluorescence-digital(QLF-D), in a sample of Korean older adults. Methods: This cross-sectional study included 67 participants, aged 65 years and older. All participants completed a questionnaire and tests to measure their manual dexterity and handgrip strength, which are parameters that indicate hand function abilities. To evaluate dental biofilm maturity, 804 surfaces of six index teeth were imaged using QLF-D and then quantified as ${\Delta}R$ values. All data were collected from May 25, 2017 to April 30, 2018. The independent t-test, one-way analysis of variance, and step-wise multiple linear regression were performed to analyze the factors associated with the maturity of dental biofilm (${\Delta}R$). Results: The multivariate linear regression analysis revealed that the factor most strongly related to dental biofilm maturity(${\Delta}R$) was manual dexterity (${\beta}=-0.326$), followed by handgrip strength (${\beta}=-0.303$) and use of interdental cleaning devices (${\beta}=-0.283$) (p<0.05). Conclusions: Manual dexterity, handgrip strength, and use of interdental cleaning devices are factors that can predict dental biofilm maturity in adults aged 65 years or older. Therefore, the hand function of a patient should be evaluated first, before assessing the oral hygiene status of the patient or providing him/her with oral health education, and the dental hygienist should provide differentiated oral hygiene care depending on the patient's hand function ability. Finally, dental hygienists should help older adults to recognize the importance of auxiliary oral hygiene devices such as interdental brushes and keep motivating them to use the devices more frequently.

• Journal of Chest Surgery
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• 제28권4호
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• pp.371-375
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• 1995

Surgical resection of lung cancer or other disease is recently required in patients with severely impaired lung function resulting from chronic obstructive pulmonary disease or disease extension. So prediction of pulmonary function after lung resection is very important in thoracic surgeon. We studied the accuracy of the prediction of postoperative pulmonary function using perfusion lung scan with 99m technetium macroaggregated albumin in 22 patients who received the pneumonectomy. The linear regression line derived from correlation between predicting[X and postoperative measured[Y values of FEV1 and FVC in patients are as follows: 1 Y[ml =0.713X + 381 in FEV1 [r=0.719 ,[P<0.01 2 Y[ml =0.645X + 556 in FVC [r=0.675 ,[P<0.01 In conclusion,the perfusion lung scan is noninvasive and very accurate for predicting postpneumonectomy pulmonary function.

• 말소리와 음성과학
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• 제5권1호
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• pp.91-98
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• 2013

This paper investigated Korean prosody as it relates to graded internal structure in an identification function. Within Korean prosody, variants regarded as dialectal variations can appear as different prosodic scales, which contain the range of within-category variations. The current experiment was intended to show how the prosodic scale corresponding to the range of within-category differences relates to f0 contours for speakers of two Korean dialects, North Kyungsang and South Cholla. In an identification task, participants responded by selecting an item from two answer choices. The probability of choosing the correct response from the two choices was computed by a logistic regression analysis using intercepts and slopes. That is, the correct response between two choices was used to show a linear line with an s-shape presentation. In this paper, to investigate the graded internal structure of labeling, 25%, 50%, and 75% of predicted probability were assessed. Listeners from North Kyungsang showed progressive variations, whereas listeners from South Cholla revealed random patterns in the internal structure of the identification function. In this paper, the results were plotted using scatterplot graphs, applying the range of within-category variation and predicted probability obtained from the logistic regression analyses. The scatterplot graphs showed the different degree of the responses for f0 scales (i.e., variations within categories). The results demonstrate that the gradient structures of native pitch accent users become more progressive in response to f0 scales.

• Journal of Information Processing Systems
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• 제12권3호
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• pp.436-454
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• 2016

This research presents the battery discharge rate models for the energy consumption of mobile phone batteries based on machine learning by taking into account three usage patterns of the phone: the standby state, video playing, and web browsing. We present the experimental design methodology for collecting data, preprocessing, model construction, and parameter selections. The data is collected based on the HTC One X hardware platform. We considered various setting factors, such as Bluetooth, brightness, 3G, GPS, Wi-Fi, and Sync. The battery levels for each possible state vector were measured, and then we constructed the battery prediction model using different regression functions based on the collected data. The accuracy of the constructed models using the multi-layer perceptron (MLP) and the support vector machine (SVM) were compared using varying kernel functions. Various parameters for MLP and SVM were considered. The measurement of prediction efficiency was done by the mean absolute error (MAE) and the root mean squared error (RMSE). The experiments showed that the MLP with linear regression performs well overall, while the SVM with the polynomial kernel function based on the linear regression gives a low MAE and RMSE. As a result, we were able to demonstrate how to apply the derived model to predict the remaining battery charge.