• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.101-101
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• 2017

근래에 대한민국 담수계에 조류 대발생으로 인한 수질악화 문재가 대두되고 있다. 또한 독성물질을 생성하는 남조류종이 우점하는 현상으로인해 수질문제와더불에 생태계와 인간의 건강도 잠재적인 위험을 받고있는 실정이다. 이와같은 조류 대발생으로인한 피해를 최소화하기위해 효과적인 수질관리가 필수적이다. 원격탐사기술은 조류의 공간적인 분포를 해석하고 농도를 정량화하기위해 이용되고 있다. 현재까지 많은 분광알고리즘들이 개발되어 담수유역에 적용이 되고 있다. 수체마다 다른 분광특성 때문에 알고리즘내의 파라미터 및 분광밴드 조정이 필수적이다. 하지만 대부분의 연구에선 파라미터와 밴드의 변경에 따른 결과향상에만 초점이 맞춰지고 있어 분광알고리즘내의 파라미터와 분광밴드사이의 관계 이해 뿐만아니라 알고리즘 최종 산출물에 대한 영향에 관한 설명이 전무한 실정이다. 본 연구에선, 대한민국 백제보를 대상으로 현장모니터링 및 조류추출 실험을 진행하였고, 이를 기반으로 5가지 클로로필a 알고리즘과 2가지 피코시아닌 알고리즘을 구축하였다. 알고리즘내에서 변수들의 관계와 영향을 알아보기위해 민감도 분석을 실시하였다. 민감도 분석 조건을 기반으로 one-objective 최적화 및 multi-objective 최적화를 실시하여 백제보수계를 대표할 수 있는 최적 변수들을 모의하였다. 민감도 분석결과 후방산란계수에 영향을 미치는 파라미터와 조류 생체량에 영향을 미치는 파라미터가 다른 변수들 및 알고리즘 농도산정결과에 가장 민감한 것으로 나타났다. multi-objective 최적화 결과가 one-objective 결과 및 reference 결과보다 대부분 정확도가 향상되었고 흡광도 계수를 함께 고려할 수 있기 때문에 백제보 수계의 분광특성을 함께 고려하여 대표할 수 있는 장점을 가지는 것으로 나타났다. 따라서, 본 연구는 민감도 분석을 활용하여 분광알고리즘 내의 변수들의 이해를 도모하였고, 최적화 기법 중, multi-objective 최적화 기법이 백제보의 분광특성을 대변하는 최적변수를 제시할 수 있음과 동시에 보다 나은 정확성을 제고할 수 있음을 확인하였다.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.329-335
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• 2010

Digital imaging detectors can use a variety of detection materials to convert X-ray radiation either to light or directly to electron charge. Many detectors such as amorphous silicon flat panels, CCDs, and CMOS photodiode arrays incorporate a scintillator screen to convert x-ray to light. The digital radiography systems based on semiconductor detectors, commonly referred to as flat panel detectors, are gaining popularity in the clinical & hospital. The X-ray detectors are described between a-Silicon based indirect type and a-Selenium based direct type. The DRS of detectors is used to convert the x-ray to electron hole pairs. Image processing is described by specific image features: Latitude compression, Contrast enhancement, Edge enhancement, Look up table, Noise suppression. The image features are tuned independently. The final enhancement result is a combination of all image features. The parameters are altered by using specific image features in the different several hospitals. The image in a radiological report consists of two image evaluation processes: Clinical image parameters and MTF is a descriptor of the spatial resolution of a digital imaging system. We used the edge test phantom and exposure procedure described in the IEC 61267 to obtain an edge spread function from which the MTF is calculated. We can compare image in the processing parameters to change between original and processed image data. The angle of the edge with respect to the axes of detector was varied in order to determine the MTF as a function of direction. Each MTF is integrated within the spatial resolution interval of 1.35-11.70 cycles/mm at the 50% MTF point. Each image enhancement parameters consists of edge, frequency, contrast, LUT, noise, sensitometry curve, threshold level, windows. The digital device is also shown to have good uniformity of MTF and image parameters across its modality. The measurements reported here represent a comprehensive evaluation of digital radiography system designed for use in the DRS. The results indicate that the parameter enables very good image quality in the digital radiography. Of course, the quality of image from a parameter is determined by other digital devices in addition to the proper clinical image.

• The Journal of the Acoustical Society of Korea
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• v.10 no.4
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• pp.5-11
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• 1991

This paper suggests a segmentation method of speech signal into phonemic units. The suggested segmentation system is speaker-independent and performed without anyprior information of speech signal. In segmentation process, we first divide input speech signal into purevoiced region and not pure voiced speech regions. After then we apply the second algorithm which segments each region into the detailed phonemic units by using the voiced detection parameters, i.e., the time variation of 0th LPC cepstrum coefficient parameter and the ZCR parameter. Types of speech, used to prove the availability of segmentation algorithm suggested in this paper, are the vocabulary composed of isolated words and continuous words. According to the experiments, the successful segmentation rate for 507 phonemic units involved in the total vocabulary is 91.7%.

• Science of Emotion and Sensibility
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• v.16 no.1
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• pp.117-124
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• 2013

This study examined that how precisely MFCC, LPC, energy, and pitch related parameters of the speech data, which have been used mainly for voice recognition system could predict the vocal emotion categories as well as dimensions of vocal emotion. 110 college students participated in this experiment. For more realistic emotional response, we used well defined emotion-inducing stimuli. This study analyzed the relationship between the parameters of MFCC, LPC, energy, and pitch of the speech data and four emotional dimensions (valence, arousal, intensity, and potency). Because dimensional approach is more useful for realistic emotion classification. It results in the best vocal cue parameters for predicting each of dimensions by stepwise multiple regression analysis. Emotion categorizing accuracy analyzed by LDA is 62.7%, and four dimension regression models are statistically significant, p<.001. Consequently, this result showed the possibility that the parameters could also be applied to spontaneous vocal emotion recognition.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.11 s.176
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• pp.16-23
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• 2005

• Proceedings of the Acoustical Society of Korea Conference
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• 1995.06a
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• pp.111-114
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• 1995

포만트 합성에 필요한 음성 파라미터를 분석하는 방법의 개선에 관하여 논한다. 내용은 주로 피치 동기 분석을 위한 피치 위치 추정법의 개선과 포만트 분석시 발생하는 스펙트럼의 왜곡 현상을 기존이 포만트 분석법 및 선형예측분방법과 비교한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.7
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• pp.1326-1331
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• 2006

Weld root gap is a important fact of a falling-off weld quality in various kind of weld defect. The welding quality can be controlled by monitoring important parameters, such as, the Arc voltage, welding current and welding speed during the welding process. Welding systems use either a vision sensor or an Arc sensor, both of which are unable to control these parameters directly. Therefore, it is difficult to obtain necessary bead geometry without automatically controlling the welding parameters through the sensors. In this paper we propose a novel approach using neural networks for detecting and monitoring of weld root gap and bead shape. Through experiments we demonstrate that the proposed system can be used for real welding processes. The results demonstrate that the system can efficiently estimate the weld bead shape and detect the welding defects.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.5 s.335
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• pp.1-8
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• 2005

A RC parallel gate model is used to consider gate distributed effect that affects RF MOSFET performance, and extraction formula based on $Y_{11}$-parameters are used to extract model parameters directly from measured S-parameters. Better agreement between measured and modeled S-parameters in the frequency range beyond 10 GHz is achieved by using the RC parallel model than conventional Rg one, demonstrating the accuracy of the RC model and extraction technique. Using these extraction methods, gate voltage dependent curves of RC gate model parameters are newly extracted, and these parameter data will greatly contribute to developing a RF nonlinear gate model.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.5 no.1
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• pp.59-64
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• 2011

In this paper, the lumped element model parameter estimation method and its implemented estimation software for fabricated floating mass transducers of IMEHDs have been presented so that the estimated parameter values could be compared with the designed ones and applied to predict the output performance when the transducers were implanted into human ears. The presented method is based on the sequential quadratic programming (SQP) for estimating parameters in the transducer's lumped model and has been implemented by the use of LabVIEW graphical language. Using the implemented estimation software, the accuracy of parameter estimation has been verified and our implemented estimation method has been evaluated by the comparison of the estimated transducer parameter values with the designed ones for a practically fabricated floating mass transducer for IMEHDs.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.3 s.43
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• pp.33-42
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• 2005

Frequency domain Volterra model is applied to nonlinear parameter identification procedure for dynamic systems modeled by nonlinear function. The frequency domain Volterra kernels, which correspond io linear, quadratic, and cubic transfer functions in lime domain, are incorporated in nonlinear parametric identification procedure. The nonlinear transfer functions, which can be derived from the Volterra series representation of the nonlinear differential equation of the system by Schetzen's method(1980), are directly used for modeling input output relation. The error is defined by the difference between the observed output and the estimated output which is calculated by substituting the observed input to nonlinear frequency domain model. The system parameters are searched by minimizing the error. Volterra model guarantees enough accuracy and convergence and the estimated coefficients have a good agreement with their actual values not only in the linear frequency region but also in the legion where the $2^{nd}\;or\;3^{rd}$ order nonlinearity is dominant.