• 대한수학회보
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• 제57권4호
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• pp.1003-1031
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• 2020

We consider the following Dirichlet initial boundary value problem with a gradient absorption and a nonlocal source $$\frac{{\partial}u}{{\partial}t}-div({\mid}{\nabla}u{\mid}^{p-2}{\nabla}u)={\lambda}u^k{\displaystyle\smashmargin{2}{\int\nolimits_{\Omega}}}u^sdx-{\mu}u^l{\mid}{\nabla}u{\mid}^q$$ in a bounded domain Ω ⊂ ℝ^N, where p > 1, the parameters k, s, l, q, λ > 0 and µ ≥ 0. Firstly, we establish local existence for weak solutions; the aim of this part is to prove a crucial priori estimate on |∇u|. Then, we give appropriate conditions in order to have existence and uniqueness or nonexistence of a global solution in time. Finally, depending on the choices of the initial data, ranges of the coefficients and exponents and measure of the domain, we show that the non-negative global weak solution, when it exists, must extinct after a finite time.

• 한국정밀공학회지
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• 제18권9호
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• pp.110-121
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• 2001

During hot pipe bending using induction heating, the wall of bending outside is thinned by tensile stress. In design requirement, the reduction of wall thickness is not allowed to exceed 12.5%. So in this study, two methods of bending, one is loading of reverse moment and the other is loading of temperature gradient, have been investigated to design pipe bending process that satisfy design requirements. For this purpose, finite element analysis with a bending radius 2Do(outer diameter of pipe) has been performed to calculate proper reverse moment and temperature gradient to be applied. Induction heating process has been analyzed to estimate influence of heating process parameters on heating characteristic by finite difference method. Then pipe bending experiments have been performed for verification of finite element and finite difference analysis results. Experimental results are in good agreement with the results of simulations.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.448-448
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• 2018

In this study, the regression models (Load ESTimator and eight-parameter model) were evaluated to estimate instantaneous pollutant loads under various criteria and optimization methods. As shown in the results, LOADEST commonly used in interpolating pollutant loads could not necessarily provide the best results with the automatic selected regression model. It is inferred that the various regression models in LOADEST need to be considered to find the best solution based on the characteristics of watersheds applied. The recently developed eight-parameter model integrated with Genetic Algorithm (GA) and Gradient Descent Method (GDM) were also compared with LOADEST indicating that the eight-parameter model performed better than LOADEST, but it showed different behaviors in calibration and validation. The eight-parameter model with GDM could reproduce the nitrogen loads properly outside of calibration period (validation). Furthermore, the accuracy and precision of model estimations were evaluated using various criteria (e.g., $R^2$ and gradient and constant of linear regression line). The results showed higher precisions with the $R^2$ values closed to 1.0 in LOADEST and better accuracy with the constants (in linear regression line) closed to 0.0 in the eight-parameter model with GDM. In hence, based on these finding we recommend that users need to evaluate the regression models under various criteria and calibration methods to provide the more accurate and precise results for pollutant load estimations.

• 한국정밀공학회지
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• 제20권7호
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• pp.138-146
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• 2003

A critical issue in area-based stereo matching lies in selecting a fixed rectangular window size. Previous stereo methods doesn't deal effectively with occluding boundary due to inevitable window-based problems, and so give inaccurate and noisy matching results in areas with steep disparity variations. In this paper, a variable window approach is presented to estimate accurate, detailed and smooth disparities for three-dimensional structure reconstruction. It makes the smoothing of depth discontinuity reduced by evaluating corresponding correlation values and intensity gradient-based similarity in the three-dimensional disparity space. In addition, it investigates maximum connected match candidate points and then devise the novel arbitrarily shaped variable window representative of a same disparity to treat with disparity variations of various structure shapes. We demonstrate the performance of the proposed variable window method with synthetic images, and show how our results improve on those of closely related techniques for accuracy, robustness, matching density and computing speed.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.284-287
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• 2003

Previous stereo methods doesn't deal effectively with depth discontinuity due to inevitable window-based problems, and so give inaccurate and noisy matching results in areas with steep disparity variations. In this paper. a variable window approach is presented to estimate accurate, detailed and smooth disparities with three-dimensional disparity space. It makes the smoothing of depth discontinuity reduced by evaluating corresponding correlation values and intensity gradient-based similarity in the space. In addition, it devises the novel arbitrarily-shaped variable window to treat with disparity variations of various structure shapes. We show how our results improve on those of closely related techniques for accuracy, robustness. matching density and computing speed.

• 비파괴검사학회지
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• 제25권3호
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• pp.189-200
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• 2005

Ultrasonic inspection methods are widely used for detecting flaws in materials. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature space. This paper describes an approach which uses LMS method to determine the coordinates of the ultrasonic probe followed by the use of SAFT to estimate the location of the ultrasonic reflector The method is employed for classifying NDE signals from the steam generator tubes in a nuclear power plant. The classification results using this scheme for the ultrasonic signals from cracks and deposits within steam generator tubes are presented.

• 대한기계학회논문집B
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• 제27권6호
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• pp.813-820
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• 2003

The purpose of this research is to develop the model of turbulence modulation due to the presence of particles in various types of particle-laden flows Available experimental data are surveyed and the dependence of turbulence modulation of carrier-phase on particle size, concentration and. particle Reynolds number are examined. This study takes into account the effect of wake produced by particle, the drag between phases and the velocity gradient in the wake to estimate the production of turbulence. The model of turbulence modulation using the mixing length theory under the assumption of equilibrium flow is proposed. Numerical results show that the model is successful in predicting the characteristics of the particle-laden in various flow conditions both qualitatively and quantitatively.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2019년도 전력전자학술대회
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• pp.380-381
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• 2019

This paper presents a grid voltage-sensorless current control design for an LCL-filtered grid-connected inverter with the purpose of enhancing the reliability and reducing the total cost of system. A disturbance observer based on the gradient steepest descent method is adopted to estimate the grid voltages with high accuracy and light computational burden even under distorted grid conditions. The grid fundamental components are effectively extracted from the estimated gird voltages by means of a least-squares algorithm to facilitate the synchronization process without using the conventional phase-locked loop. Finally, the estimated states of inverter system obtained by a discrete current-type full state observer are utilized in the state feedback current controller to realize a stable voltage-sensorless current control scheme. The effectiveness of the proposed scheme is validated through the simulation results.

• Communications for Statistical Applications and Methods
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• 제31권2호
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• pp.203-212
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• 2024

The area under the ROC curve (AUC) is one of the most common criteria used to measure the overall performance of binary classifiers for a wide range of machine learning problems. In this article, we propose a L₁-penalized AUC-optimization classifier that directly maximizes the AUC for high-dimensional data. Toward this, we employ the AUC-consistent surrogate loss function and combine the L₁-norm penalty which enables us to estimate coefficients and select informative variables simultaneously. In addition, we develop an efficient optimization algorithm by adopting k-means clustering and proximal gradient descent which enjoys computational advantages to obtain solutions for the proposed method. Numerical simulation studies demonstrate that the proposed method shows promising performance in terms of prediction accuracy, variable selectivity, and computational costs.

• 한국산학기술학회논문지
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• 제12권7호
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• pp.2925-2930
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• 2011

최근의 차량 연비는 고가의 연료 가격과 환경 규제 등으로 인하여 중요한 문제로 대두되었다. 전기, 전자, 기계 등의 기술 발달에 힘입어 연비는 많이 개선되었으나 현재도 연비 측정은 주어진 모드(LA-4, FTP-75 등)에서 컴퓨터 모의시험 및 다이나모에서 수행한다. 이러한 연비는 실제 도로 주행 연비와 차이가 발생한다. 그 주요 원인중의 하나는 도로의 경사를 고려하지 않았기 때문이다. 본 논문에서는 경사가 포함된 고속도로에서 경사가 연비에 미치는 영향을 평가하기 위하여 경사가 포함된 영동고속도로를 주행하여 연료 소모량을 측정하고 연비를 계산한다. 또한 같은 도로를 경사가 없다고 가정하여 주행한 연비와 비교 분석한다. 이때 두 경우의 연료 소모량 차이에 의해 발생된 총 발생 에너지를 계산하고, 모의실험에서 타이어 구동력으로 부터 발생한 엔진 토크와 파워 데이터로부터 구동력에 소모된 에너지를 계산한다. 이제 도로의 경사 때문에 소모된 연료에 의해 발생된 총 발생에너지와 구동력에 사용된 에너지와의 관계를 검증한다. 또한 결론에서는 경사를 갖는 자동차 전용도로에서 경사에도 불구하고 연비를 향상할 수 있는 방안을 제시한다.