• 조명전기설비학회논문지
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• 제12권2호
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• pp.69-76
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• 1998

본 논문에서는 배압터빈과 추기복수터빈으로 이루어진 열병합 발전플랜트의 최전운전을 결정할 수 있는 새로운 알고리즘을 제시한다. 제시한 알고리즘은 플랜트가 운전중에 직접 온 라인으로 취할 수 있는 증가량만을 파라메타로 하여 보일러와 터빈-발전기의 최적부하를 결정할 수 있다. 본 알고리즘은 비선형 경비함수와 해당 제한사항들로 이루어져 있으며 실제 운전중인 열병합 발전플랜트와 비교 시뮬레이션을 실시한 결과 만족할만한 결과를 얻었다. 즉 실제 운전 데이터와 비교해본 결과 공정의 증기 부하량에 따라 1.2∼4.5[%]의 운전경비 절감효과를 얻을 수 있었다. 또한 본 알고리즘은 필요한 입력 데이터를 공정으로부터 쉽게 온 라인으로 취할 수 있어 프로세스 컴퓨터로 용이하게 구현할 수 있다.

• Bulletin of the Korean Chemical Society
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• 제33권7호
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• pp.2320-2324
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• 2012

A novel approach for metabolite extraction and fingerprinting was introduced based upon the nano-baskets and emulsion liquid membrane-nuclear magnetic resonance (ELM-NMR) technique. The objective of this method is optimizing the fingerprints, minimizing the metabolic variation from analysis, increasing the likelihood differences, and obtaining the maximum extraction yield. Low molecular weight metabolites in rat serum were recovered by ELMs using 12 nano-baskets of calixarene, as both emulsifier and carrier. The yields of ELMs were optimized by the method of one-at-a-time. According to NMR data, the maximum metabolic variation was achieved using scaffold 4 (4 wt %), n-decane membrane, stirring rate of 300 rpm, treat and phase ratios of 0.3 and 0.8, respectively. The results revealed that some calixarenes tend to extract non-specific macromolecules; and repeatability of fingerprints for 7-mediated ELM was maximum and for 3-mediated ELM was minimum. The yield of extractions was obtained to be higher for n-decane and lower for carbon tetrachloride. Among different membranes, the fingerprints by chlorinated liquid membranes were more repeatable than using toluene or n-decane.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 3부
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• pp.172-177
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• 2008

생체 인식은 개인의 고유한 생체 정보를 획득하여 개인 식별에 이용하는 기술로, 그중 얼굴 인식은 사용자의 편의성과 비강제성이라는 장점이 있는 응용기술로 평가 받고 있다. 본 논문에서는 얼굴인식 기술동향을 살펴보고 얼굴 영역 추출, 특정 추출, 매칭을 포함한 시스템에 대해 논한다. 얼굴 영역 추출에는 얼굴 형판 정합 방법과 얼굴 요소의 검출에 의한 방법을, 특정 추출에서는 PCA 와 LDA 등의 방법을, 그리고 매칭을 통한 인증 단계에서는 최근접 분류기를 소개한다. 다양한 얼굴 인식 기법들이 제시됨에 따라 공인된 성능 평가 방법이 필요하게 되는데, 대용량 표준 얼굴 DE의 구축과 얼굴 인식 성능 평가 방법 개발의 필요성을 제시한다. 향후 얼굴인식 시스템에서는 조명, 자세, 표정의 변화를 어떻게 보정하여 인식 할 것인가 하는 것이 연구되어야 할 핵심 분야로서 3차원 얼굴 영상 복원 기술을 통한 해결방법을 살펴본다.

• 정보처리학회논문지D
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• 제17D권1호
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• pp.59-66
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• 2010

기존의 OCR 엔진은 보정된 환경에서 읽혀진 서류 영상에 맞게 설계되어있다. 스마트 폰을 비롯한 검정 화면 거리가 보정되지 않은 기기에서 읽혀진 영상에서는 삼차원 원근 투시에 의한 찌그러짐 또는 곡면상에서의 찌그러짐 등이 핵심적인 문제점들로 여겨진다. 휴대용 단말기에서 읽혀진 영상들에서의 OCR 기능에 대한 요구가 증가일로에 있는 시점에서, 본 논문에서는 문제점들을 세 가지로 구분하고 - 회전에 무관한 문자 영역 추출, 폰트 등의 크기에 무관한 문자 선 영역 추출, 3차원 매핑 이론 - 이를 해결하기위한 방법을 제시하였다. 이러한 방법론을 통합하여 카메라 영상 위에서의 OCR을 개발하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.241-243
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• 2003

This paper presents an algorithm that automatically extracts buildings among many different features on the earth surface by fusing LIDAR data with panchromatic aerial images. The proposed algorithm consists of three stages such as point level process, polygon level process, parameter space level process. At the first stage, we eliminate gross errors and apply a local maxima filter to detect building candidate points from the raw laser scanning data. After then, a grouping procedure is performed for segmenting raw LIDAR data and the segmented LIDAR data is polygonized by the encasing polygon algorithm developed in the research. At the second stage, we eliminate non-building polygons using several constraints such as area and circularity. At the last stage, all the polygons generated at the second stage are projected onto the aerial stereo images through collinearity condition equations. Finally, we fuse the projected encasing polygons with edges detected by image processing for refining the building segments. The experimental results showed that the RMSEs of building corners in X, Y and Z were ${\pm}$8.1㎝, ${\pm}$24.7㎝, ${\pm}$35.9㎝, respectively.

• Biotechnology and Bioprocess Engineering:BBE
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• 제6권6호
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• pp.426-432
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• 2001

Perstractive fermentation is a good way to increase the productivity of bioreactors. Us-ing Propionibacteria as the model system, the feasibility of using supported emulsion liquid mem-brane(SELM) fro perstractive fermentation is assessed in this study. Five industrial solvents were considered as the solvent for perparing the SELM. The more polar a solvent, is the higher the par-tition coefficeint However, toxicity of a solvent also increases with its polarity. CO-1055(indus-trial decanol/octanol blend)has the highest partition coefficient toward propionic acid among the solvents that has no molecular toxicity toward Propionibacteria, A preliminary extraction study was conducted using tetradecane as solvent in a hydrophobic hollow fiber contactor. The results confirmed that SELM eliminates the equilibrium limitation of conventional liquid-liquid extrac-tion and allows the use of a non-toxic solvent with low partition coefficient.

• 대한음성학회지:말소리
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• 제61호
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• pp.63-74
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• 2007

Discrimination of music and speech from the multimedia signal is an important task in audio coding and broadcast monitoring systems. This paper deals with the problem of feature parameter extraction for discrimination of music and speech. The wavelet transform is a multi-resolution analysis method that is useful for analysis of temporal and spectral properties of non-stationary signals such as speech and audio signals. We propose new feature parameters extracted from the wavelet transformed signal for discrimination of music and speech. First, wavelet coefficients are obtained on the frame-by-frame basis. The analysis frame size is set to 20 ms. A parameter $E_{sum}$ is then defined by adding the difference of magnitude between adjacent wavelet coefficients in each scale. The maximum and minimum values of $E_{sum}$ for period of 2 seconds, which corresponds to the discrimination duration, are used as feature parameters for discrimination of music and speech. To evaluate the performance of the proposed feature parameters for music and speech discrimination, the accuracy of music and speech discrimination is measured for various types of music and speech signals. In the experiment every 2-second data is discriminated as music or speech, and about 93% of music and speech segments have been successfully detected.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권3호
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• pp.175-184
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• 2008

To construct user profiles automatically, an extraction method for representative keywords from a set of documents is needed. In our previous works, we suggested such a method and showed its usefulness. Here, we apply it to the classification problem and observe how much it contributes to performance improvement. The method can be used as a linear document classifier with few modifications. So, we first evaluate its performance for that case. The method is also applicable to some non-linear classification methods such as GIS (Generalized Instance Set). In GIS algorithm, generalized instances are built from training documents by a generalization function and then the K-NN algorithm is applied to them, where the method can be used as a generalization function. For comparative works, two famous linear classification methods, Rocchio and Widrow-Hoff algorithms, are also used. Experimental results show that our method is better than the others for the case that only positive documents are considered, but not when negative documents are considered together.

• Smart Structures and Systems
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• 제25권3호
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• pp.265-277
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• 2020

Recently, the concept of "drive-by" bridge monitoring system using indirect measurements from a passing vehicle to extract key parameters of a bridge has been rapidly developed. As one of the most key parameters of a bridge, the natural frequency has been successfully extracted theoretically and in practice using indirect measurements. The frequency of bridge is generally calculated applying Fast Fourier Transform (FFT) directly. However, it has been demonstrated that with the increase in vehicle velocity, the estimated frequency resolution of FFT will be very low causing a great extracted error. Moreover, because of the low frequency resolution, it is hard to detect the frequency drop caused by any damages or degradation of the bridge structural integrity. This paper will introduce a new technique of bridge frequency extraction based on Hilbert Transform (HT) that is not restricted to frequency resolution and can, therefore, improve identification accuracy. In this paper, deriving from the vehicle response, the closed-form solution associated with bridge frequency removing the effect of vehicle velocity is discussed in the analytical study. Then a numerical Vehicle-Bridge Interaction (VBI) model with a quarter car model is adopted to demonstrate the proposed approach. Finally, factors that affect the proposed approach are studied, including vehicle velocity, signal noise, and road roughness profile.

• 통합자연과학논문집
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• 제11권4호
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• pp.167-183
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• 2018

Electroencephalogram (EEG) recording provides a new way to support human-machine communication. It gives us an opportunity to analyze the neuro-dynamics of human cognition. Machine learning is a powerful for the EEG classification. In addition, machine learning can compensate for high variability of EEG when analyzing data in real time. However, the optimal EEG electrode location must be prioritized in order to extract the most relevant features from brain wave data. In this paper, we propose an intelligent system model for the extraction of EEG data by training the optimal electrode location of EEG in a specific problem. The proposed system is basically a fuzzy system and uses a neural network structurally. The fuzzy clustering method is used to determine the optimal number of fuzzy rules using the features extracted from the EEG data. The parameters and weight values found in the process of determining the number of rules determined here must be tuned for optimization in the learning process. Genetic algorithms are used to obtain optimized parameters. We present useful results by using optimal rule numbers and non - symmetric membership function using EEG data for four movements with the right arm through various experiments.