• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집B
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• pp.54-58
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• 2001

The measurement method of the spectral emissivity by using hemispherical mirror which has an inclined observation hole is studied. This method is useful in measuring the spectral emissivity of the solid material both conductor and non-conductor. In this study, the effective reflectivity of the hemispherical mirror is also measured for calculating the spectral emissivity of materials. The effective reflectivity measured is 0.9.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2007년도 정기 학술대회 논문집
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• pp.789-794
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• 2007

Recently, the necessity of efficient and exact method to analyze structures is increasing with the importance of the seismic analysis. But the finite element method used in many field do not give the exact solution unless the length of the element is very short enough to represent the deformation of the element. Because the amount of computer calculation increase with the increasing of the number of degree of freedoms, the finite element method for the exact dynamic analysis of structures would not be efficient. To solve these problems, spectral clement method combined spectral method using the principle of wave mechanics and finite element method for the analysis of discrete models is applied to evaluate the behavior of the spatial structures. As a result of analysis. it becomes clear that the spectral element method is faster and more exact than the finite clement method.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.1654-1659
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• 2003

This paper introduces a fast Fourier transform (FFT)-based spectral analysis method for the transient responses as well as the steady-state responses of linear discrete systems. The force vibration of a viscously damped three-DOF system is considered as the illustrative numerical example. The proposed spectral analysis method is evaluated by comparing with the exact analytical solutions as well as with the numerical solutions obtained by the Runge-Kutta method.

• 한국컴퓨터정보학회논문지
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• 제22권10호
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• pp.27-34
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• 2017

In this paper, we propose a novel radiometric calibration method which can effectively compensate the nonlinearity of the detector for hyper-spectral camera. In general, the detector of hyper-spectral camera can produce nonlinear output depending on radiance and integral time. The conventional radiometric calibration methods extract the imprecise radiance profile from the spectral profile of the target due to this nonlinearity. In our proposed method, we use a quadratic equation instead of a linear equation to describe the relation between output of detector and radiance. Then, we use a fractional function to compensate variation of integration time. Thus, our proposed method can extract more precise spectral profile of radiance than conventional radiometric calibration method.

• International Journal of Control, Automation, and Systems
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• 제4권5호
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• pp.592-600
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• 2006

The pattern recognition of the complicated grasping operation based on electroencephalography (simply named as EEG) is very helpful on realtime control of the robotic hand. In the paper, a new spectral feature analysis method based on Band Pass Filter (simply named as BPF) and Power Spectral Analysis (simply named as PSA) is presented for discriminating the complicated grasping operations. By analyzing the spectral features of grasping operations with the use of the two-channel EEG measurement system and the pattern recognition of the BP neural network, the degree of recognition by the traditional spectral feature method based on FFT and the new spectral features method based on BPF and PSA could be compared. The results show that the proposed method provides highly improved performance than the traditional one because the new method has two obvious advantages such as high recognition capability and the fast learning speed.

• 한국대기환경학회지
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• 제7권3호
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• pp.189-196
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• 1991

In recent years spectral methods have been found to be a powerful tool for the numerical solution of hynamic differential equations. The main attraction of spectral method is accuracy even though it is generally difficult to implement and solve the complex problems using spectral method. We introduced diffusion equations describing the state of air pollution and solved by pseutospectral method in dimensionless form. The results were compared with both those of other numerical methods and analytical solutions. Comparing with finite difference method and finite element method, spectral method shows the highest accuracy for one dimension problem in this study. Also, the results of two dimensional diffusion problems show good agreement with analytical solutions.

• 한국컴퓨터정보학회논문지
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• 제21권11호
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• pp.1-7
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• 2016

In this paper, we proposed real-time relative radiometric calibration processing method for SWIR(Short Wavelength Infra-Red) sensor using 'Hyper-Spectral Imager'. Until now domestic research for Hyper-Spectral Imager has been performing with foreign sensor device. So we have been studying hyper spectral sensor device to meet domestic requirement, especially military purpose. To improve detection & identify capability in 'Hyper-Spectral Imager', it is necessary to expend sensing wavelength from visual and NIR(Near Infra-Red) to SWIR. We aimed to design real-time processor for SWIR sensor which can control the sensor ROIC(Read-Out IC) and process calibrate the image. To build Hyper-Spectral sensor device, we will review the SWIR sensor and its signal processing board. And we will analyze relative radiometric calibration processing method and result. We will explain several SWIR sensors, our target sensor and its control method, steps for acquisition of reference images and processing result.

• Current Optics and Photonics
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• 제5권5호
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• pp.562-575
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• 2021

As a new type of spectrometer, that based on filters with different transmittance features attracts a lot of attention for its advantages such as small-size, low cost, and simple optical structure. It uses post-processing algorithms to achieve target spectrum reconstruction; therefore, the performance of the spectrometer is severely affected by noise. The influence of noise on the spectral reconstruction results is studied in this paper, and suggestions for solving the spectral reconstruction problem under noisy conditions are given. We first list different spectral reconstruction methods, and through simulations demonstrate that these methods show unsatisfactory performance under noisy conditions. Then we propose to apply the gradient projection for sparse reconstruction (GRSR) algorithm to the spectral reconstruction method. Simulation results show that the proposed method can significantly reduce the influence of noise on the spectral reconstruction process. Meanwhile, the accuracy of the spectral reconstruction results is dramatically improved. Therefore, the practicality of the filter-based spectrometer will be enhanced.

• ETRI Journal
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• 제44권5호
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• pp.769-779
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• 2022

Spectral clustering has become a typical and efficient clustering method used in a variety of applications. The critical step of spectral clustering is the similarity measurement, which largely determines the performance of the spectral clustering method. In this paper, we propose a novel spectral clustering algorithm based on the local similarity measure of shared neighbors. This similarity measurement exploits the local density information between data points based on the weight of the shared neighbors in a directed k-nearest neighbor graph with only one parameter k, that is, the number of nearest neighbors. Numerical experiments on synthetic and real-world datasets demonstrate that our proposed algorithm outperforms other existing spectral clustering algorithms in terms of the clustering performance measured via the normalized mutual information, clustering accuracy, and F-measure. As an example, the proposed method can provide an improvement of 15.82% in the clustering performance for the Soybean dataset.

• Structural Engineering and Mechanics
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• 제75권3호
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• pp.311-325
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• 2020

In applying the spectral stochastic finite element methods to the frequency response analysis, the conventional methods are known to give unstable and inaccurate results near the natural frequencies. To address this issue, a new sensitivity based stabilized formulation for stochastic frequency response analysis is proposed in this paper. The main difference over the conventional spectral methods is that the polynomials of random variables are applied to both numerator and denominator in approximating the harmonic response solution. In order to reflect the resonance behavior of the structure, the denominator polynomials is constructed by utilizing the natural frequency sensitivity and the random mode superposition. The numerator is approximated by applying a polynomial chaos expansion, and its coefficients are obtained through the Galerkin or the spectral projection method. Through various numerical studies, it is seen that the proposed method improves accuracy, especially in the vicinities of structural natural frequencies compared to conventional spectral methods.