• Journal of the Korean Chemical Society
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• v.54 no.1
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• pp.13-22
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• 2010

The photophysical properties of 7-diethylaminocoumarin (DEAC) laser dye have been measured in different solvents. The emission spectrum of DEAC has also been measured in cationic (CTAC) and anionic (SDS) micelles. The laser parameters have been calculated in different solvents namely acetone, dioxane, ethanol and dimethylforamide(DMF). The photoreactivity of DEAC has been studied in $CCl_4$ solvent using 366 nm light. The values of photochemical yield (${\Phi}_c$) and rate constant (k) are determined. The interaction of organic acceptors such as picric acid (PA), tetracyanoethylene (TCNE) and 7,7,8,8-tetracynoquinonedimethane (TCNQ) with DEAC are also studied using fluorescence measurements in acetonitrile ($CH_3CN$). The electrochemical investigation of (DEAC) has been carried out using cyclic voltammetry and convolutive voltammetry combined with digital simulation technique at a platinum electrode in 0.1 mol $L^{-1}$ tetrabutyl ammonium perchlorate (TBAP) in $CH_3CN$ solvent. The electrochemical parameters of the investigated compound were determined using cyclic and convolutive voltammetry. The extracted electrochemical parameters were verified and confirmed via digital simulation method.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.5
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• pp.549-555
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• 2001

Ultrasonic is a powerful nondestructive technique for getting the information of flaws and material properties of in-services facilities. We prepared 4 different 1Cr-1Mo-0.25V specimens by Isothermal aging at $630^{\circ}C$. We evaluated material degradation using ultrasonic parameters, velocity, attenuation and harmonic generation. Attenuation and nonlinear parameter derived from harmonic generation efficiency increased as degradation. Especially the second harmonic of the fundamental wave in the 1,820h aging material was observed to exceed 20dB more than that in the un-aged material. But velocity remained virtually the same for all specimens. We concluded that nonlinear parameter and attenuation are sensitive to material degradation, but velocity was not. It'll be a good parameter for evaluating the material degradation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.5
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• pp.413-420
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• 2021

This study is about a machine learning model for predicting insufficient parameters through other parameters when one of the collected parameters is insufficient. A regression model was created to predict time, temperature, humidity, CO2, and light quantity data through the machine learning regression analysis function in Matlab. In addition, the three models with the lowest RMSE values for each parameter were selected and verified. For verification, the predicted values were obtained by applying the test data to the prediction model derived from each parameter, and the correlation coefficient and error average between the measured values and the obtained predicted values were obtained and then compared.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.2
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• pp.165-173
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• 2011

The acoustic emission(AE) technique is a well established method to carry out structural health monitoring(SHM) of large structures. However, the real-time monitoring of the crack growth in the roller coaster support structures is not easy since the vehicle operation produces very large noise as well as crack growth. In this investigation, we present the waveform parameter filtering method to classify acoustic sources in real-time. This method filtrates only the AE hits by the target acoustic source as passing hits in a specific parameter band. According to various acoustic sources, the waveform parameters were measured and analyzed to verify the present filtering method. Also, the AE system employing the waveform parameter filter was manufactured and applied to the roller coaster support structure in an actual amusement park.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.7 no.2
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• pp.41-50
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• 1993

This paper describes an effort to develop a microcomputer-based parameter identification system for three phase and two phase brushless DC motor. Back EMF equation is derived from back EMF waveform of three phase and two phase brushless DC motor. In this paper, a new identification algorithm for the brushless DC motor parameters by Pasek's technique is developed. It is found that Pasek's equation is valid for the brushless DC motor, too. The results obtained clearly shows that it is possible to implement the identification system for the determination of the brushless DC motor parameters. To minimize errors due to the ripple component in the measured armature current, digital averaging firis employed. The whole identification process of signal generation, measuring, parameter determination is fully automated. The use of the propod method in the parameter identifition system shows that the averaged current curve is in excellent agreement with the estimated current curve. Therefore, this close agreement confirms the validity of this technique.

• Journal of the Earthquake Engineering Society of Korea
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• v.16 no.1
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• pp.27-35
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• 2012

In this study, the ground motion was synthesized using the finite fault model by the stochastic green function method, and the difference in the ground motions was evaluated by using various values of the source parameters. An earthquake with a moment magnitude of 6.5 was assumed for the example fault model. The distribution of the slip in the fault plane was calculated using the statistical data of the asperity area. The source parameters considered in this study were the location of the hypocenter in the fault plane and the ratio of the rupture to the shear wave velocity, the rise time, the corner frequency of the source spectrum, and a high frequency filter. The values of the parameters related to the stochastic element source model were adjusted for different tectonic regions, and the others were selected for several possible cases. The response spectra were constructed from the synthesized ground motion time history and compared with the different parameter values. The frequency range affected by each parameter and the differences of the spectral accelerations were evaluated.

• Journal of the Korea Computer Graphics Society
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• v.26 no.5
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• pp.15-24
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• 2020

We present a supervised learning method that estimates the simulation parameters required to simulate the fabric from the static drape shape of a given fabric sample. The static drape shape was inspired by Cusick's drape, which is used in the apparel industry to classify fabrics according to their mechanical properties. The input vector of the training model consists of the feature vector extracted from the static drape and the density value of a fabric specimen. The output vector consists of six simulation parameters that have a significant influence on deriving the corresponding drape result. To generate a plausible and unbiased training data set, we first collect simulation parameters for 400 knit fabrics and generate a Gaussian Mixed Model (GMM) generation model from them. Next, a large number of simulation parameters are randomly sampled from the GMM model, and cloth simulation is performed for each sampled simulation parameter to create a virtual static drape. The generated training data is fitted with a log-linear regression model. To evaluate our method, we check the accuracy of the training results with a test data set and compare the visual similarity of the simulated drapes.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1331-1336
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• 2023

In text-based fish disease classification using machine learning, there is a problem that the input parameters of the machine learning model are too many, but due to performance problems, the input parameters cannot be arbitrarily reduced. This paper proposes a method of optimizing input parameters specialized for Paralichthys olivaceus disease classification using SHAP analysis techniques to solve this problem,. The proposed method includes data preprocessing of disease information extracted from the halibut disease questionnaire by applying the SHAP analysis technique and evaluating a machine learning model using AutoML. Through this, the performance of the input parameters of AutoML is evaluated and the optimal input parameter combination is derived. In this study, the proposed method is expected to be able to maintain the existing performance while reducing the number of input parameters required, which will contribute to enhancing the efficiency and practicality of text-based Paralichthys olivaceus disease classification.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.801-804
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• 2001

LSP 파라미터는 음성코덱(codec)이나 인식기에서 음성 신호를 분석하여 전송형이나 저장형 파라미터로 변환되어, 주로 저전송률 음성부호화기에 사용된다. 그러나 LPC 계수를 LSP로 변환하는 방법이 복잡하여 계산시간이 많이 소요된다는 단점이 있다[1]. 기존의 LSP 변환 방법 중 음성 부호화기에서 주로 사용하는 real root 방법은 근을 구하기 위해 주파수 영역을 순차적으로 검색하기 때문에 계산시간이 많이 소요되는 단점을 갖는다. 본 논문에서 비교 평가한 알고리즘은 첫 번째, 기존의 real root 알고리즘, 두 번째는, LSP 파라미터의 분포 특성을 조사하여 이를 토대로 검객구간의 순서와 검색간격을 달리한 경우, 세 번째는 검색 시 mel scale을 사용한 알고리즘이다. 실험결과, 기존의 real root 방식에 비하여 두 가지 방식 모두가 변환시간의 40% 이상이 감소되는데 반하여 통일한 관을 찾음을 알 수가 있었고, 특히 분포특성을 이용하여 검색순서와 간격조절을 한 경우에 있어서, 기존의 방식보다 40%이상이 감소되었다.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.557-560
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• 2000

LSP 파라미터는 일정한 ,스펙트럼 민감도와 낮은 스펙트럼 왜곡을 보이고 선형보간이 용이하다는 장점을 갖는다. 피러나 LPC 계수를 LSP 파라미터로 변환하는 방법이 복잡하여 계산시간이 많이 소요된다. 기존의 LSP 변환 방법 중 음성 부호화기에 주로 사용되는 Real Root 방법은 근을 구하기 위해 주파수 역을 순차적으로 검색하기 때문에 계산시간이 많이 소요된다. 본 논문에서 제안하는 방법은 음성 특성을 이용하는 것으로, 묵음의 경우는 묵음 구간에서 일정하게 나타나는 LSP 파라미터의 분포 특성을 이용하여 검색하고 유/무성음에 대해서는 LSP 파라미터의 분포도에 따라 검색구간의 순서와 검색간격을 달리한다. 또한, 모음에 대해서는 제1 포만트와 제2 포만트의 연관성을 고려하여 검색구간을 조절한다. 기존의 Real Root 방법과 제안한 방법을 비교한 결과 검색시간이 평균 46.5％ 단축되었다.