• 한국음향학회지
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• 제27권3호
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• pp.119-128
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• 2008

본 논문에서는 대역폭 확장 (Bandwidth Extension, BWE)을 위한 대표적인 통계적 방법인 가우스 혼합 모델 (Gaussian Mixture Model, GMM) 방법과 은닉마코프 모델 (Hidden Markov Model, HMM) 방법의 관계를 분석하고 성능을 비교한다. HMM 방법은 GMM 방법과 달리 기억능력을 가진 시스템으로서 인접한 음성 프레임간의 상관성을 모델링하고 이를 BWE 시스템에 활용한다는 장점을 가진다. 따라서 원래 신호의 프레임간 스펙트럼 변화특성을 보다 잘 추정할 수 있으리라 예상할 수 있다. 이 점을 확인하기 위해 정적 측도 외에 음성 스펙트럼의 일차 도 함수와 관련된 동적 측도를 적용하였다. 성능평가 결과, 정적 측도 관점에서는 두 방법은 대등한 성능을 보였지만 동적 측도 관점에서는 HMM 방법이 우수한 성능을 보였다. 또한 이러한 차이는 HMM 모델의 상태 수에 비례하여 증가함을 확인할 수 있었다. 이와 같은 실험결과는 HMM 방법이 적어도 'blind BWE' 문제에 있어서 적절한 해법임을 시사한다. 한편, 동적 측도의 관점에서는 비록 열세로 나타났지만 GMM 방법은 상대적으로 단순하다는 장점을 가지고 있으며 특히, 정적 측도에 있어서 HMM 방법과 대등하다는 사실은 응용분야에 따라서는 HMM 방법의 효과적인 대안이 될 수 있음을 시사한다.

• ETRI Journal
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• 제35권1호
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• pp.100-108
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• 2013

In this paper, a feature extraction (FE) method is proposed that is comparable to the traditional FE methods used in automatic speech recognition systems. Unlike the conventional spectral-based FE methods, the proposed method evaluates the similarities between an embedded speech signal and a set of predefined speech attractor models in the reconstructed phase space (RPS) domain. In the first step, a set of Gaussian mixture models is trained to represent the speech attractors in the RPS. Next, for a new input speech frame, a posterior-probability-based feature vector is evaluated, which represents the similarity between the embedded frame and the learned speech attractors. We conduct experiments for a speech recognition task utilizing a toolkit based on hidden Markov models, over FARSDAT, a well-known Persian speech corpus. Through the proposed FE method, we gain 3.11% absolute phoneme error rate improvement in comparison to the baseline system, which exploits the mel-frequency cepstral coefficient FE method.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.126-129
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• 2005

Change detections is carried out under the assumption that pixel boundaries of geometrically corrected time series satellite images cover the same location. However that assumption can be wrong when shifts in the pointing direction of a satellite sensor occurs. Currently, although the influence of misregistration on landcover change detection has been investigated, there has been little research on the influence of pointing direction shifts of a satellite sensor. In this study, a simple method for reducing the effects of pointing direction shifts of a satellite sensor is proposed: the classification of two ASTER images was carried out using the linear spectral mixture analysis, the two classification results were resampled into a geometrically fixed grid, and then the change detection of the two ASTER images was carried out by comparing the resampled classification results of the two images. The proposed method showed high performance in discriminating between changed areas and unchanged areas by removing the pointing direction shifts of a satellite sensor.

• 한국염색가공학회:학술대회논문집
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• 한국염색가공학회 2011년도 제44차 학술발표회
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• pp.35-35
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• 2011

The design and preparation of novel dye rotaxanes have gained much interest recently, since such structure usually exhibits peculiar spectral and optical changes. In spite of the promising results to date, increasing pressure remains to develop novel supramolecular structures based on stimuli-responsive systems. This presentation covers the study of inclusion complexes of cyclodextrins and various chromophores, with an emphasis on our most recent outcome of anisotropic hydrogel. In this system, physical gelation prepared from simple mixture of CD and a azo dye is completed through specific host-guest interaction. The obtained hydrogel exhibits respective morphological transitions based on supramolecular assembly and dissociation, leading to either precipitation or a sol-to-gel transition. It can identify different classes of metal ions, and, among them, naked-eye differentiation of lead ion is possible due to the coordination-induced unthreading of dye molecules. Accompanying structural changes were verified by numerous characterization techniques, including 2D-ROESY, HR-MAS, UV-Visible absorption, small-angle X-ray scattering, and induced circular dichroism measurements. Such properties discussed here will find useful in analytical applications, such as metal ion sensing and removal applications.

• 한국응용약물학회:학술대회논문집
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• 한국응용약물학회 1996년도 춘계학술대회
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• pp.168-168
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• 1996

가는잎쇄기풀(Urtica angustifolia Fisch.)은 쇄기풀과(Urticaceae)에 속하는 다년생 초본으로 중약 또는 민간에서 동속 근연식물과 함께 전초를 담마라하여 류마치스성 동통, 산후의 산풍, 소아의 추풍, 경풍,담마진의 치료에 사용되고 있다. Rat에서 실험적 항당뇨 효과를 검토해본 결과 혈당강하 작용이 있는 본 식물로부터 그 혈당강하 성분의 분리에 앞서 식물화학 성분을 규명하고자 본 실험에 착수하였다. 가는잎쇄기풀 전초의 MeOH ex.를 CH$_2$Cl$_2$, EtOAc, n-BuOT 및 $H_2O$로 분획하고 각종 column chromatography를 통하여 다수의 화합물을 분리하였다. 각 화합물은 이화학적 성상 및 spectral data로부터 scopoletin, esculetin dimethyl ether(scoparone), sterol mixture, $\beta$-sitosteryl-3-o-glucoside, kaempferol-3-o-glucoside, quercetin-3-o-glucoside, kaempferol-3-o-rutinoside로 확인하였으며 그 외 다수의 화합물은 그 구조를 규명중이다.

• Journal of Astronomy and Space Sciences
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• 제17권1호
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• pp.11-18
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• 2000

We have modeled the observed spectral energy distributions(SEDs) of young stellar objects (YSOs) in giant molecular clouds (GMCs). We propose the theoretical modles for the dust envelopes around YSOs. The YSOs in a GMC may share the same initial chemical composition. In this paper, we compare the model SEDs with the observations of the YSOs. Dust shells of the YSOs are composed of a mixture of astronomical silicate and graphite grains. We propose the models for the evolution of the GMCs comparing the shape of the SEDs on the IRAS 2-color diagram with the age.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 춘계학술대회 논문집
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• pp.206-209
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• 2006

강우-유출 모델링에 있어 토지피복/이용 상태는 중요한 입력변수로 사용되지만 기존의 다중분광영상을 이용한 분류에는 한계가 있다. 본 연구에서는 위성탑재 초분광영상인 Hyperion 영상의 분광혼합분석을 통해 도시지역의 수문학적 토지피복/이용 분류를 실시하였으며 분류등급의 기준은 널리 사용되고 있는 SCS 토지피복/이용 등급을 이용하였다. 정확도분석을 위해 항공사진을 디지타이징하여 불투수면적의 비율을 비교하였으며 분광혼합분석 결과와 항공사진에서 불투수면적의 비율은 유사하게 나타났다. 그러나 SCS의 분류등급은 미국을 기준으로 개발되었기 때문에 임계치를 이용하여 분류된 등급과 실제 항공사진판독의 결과가 일부 다르게 나타나는 것을 알 수 있었다.

• ETRI Journal
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• 제39권1호
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• pp.21-29
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• 2017

This paper addresses the problem of unsupervised speech separation based on robust non-negative matrix factorization (RNMF) with ${\beta}$-divergence, when neither speech nor noise training data is available beforehand. We propose a robust version of non-negative matrix factorization, inspired by the recently developed sparse and low-rank decomposition, in which the data matrix is decomposed into the sum of a low-rank matrix and a sparse matrix. Efficient multiplicative update rules to minimize the ${\beta}$-divergence-based cost function are derived. A convolutional extension of the proposed algorithm is also proposed, which considers the time dependency of the non-negative noise bases. Experimental speech separation results show that the proposed convolutional RNMF successfully separates the repeating time-varying spectral structures from the magnitude spectrum of the mixture, and does so without any prior training.

• Rapid Communication in Photoscience
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• 제4권2호
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• pp.34-36
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• 2015

New spectroscopic characteristics of amorphous ferric hydroxide ($Fe(OH)_3$), interestingly in the near infrared (NIR) region, are presented in this study. The absorption spectrum of ferric hydroxide covers wide spectral regions from ultraviolet to NIR (200~900 nm). Unique emission bands were newly observed in the NIR regions (800~1400 nm). Several bands of this NIR emission are quiet well overlapped with the combinational vibrational absorption bands of water. From photothermal conversion study, very interestingly, temperature of aqueous mixture solution including the amorphous ferric hydroxide was significantly increased from ambient temperature to $38^{\circ}C$ for 30 minutes under irradiation of a standard helium lamp.

• 대한음성학회지:말소리
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• 제67호
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• pp.167-180
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• 2008

This paper describes a novel spectral envelope conversion method based on Gaussian mixture model (GMM). The core of this paper is rearranging source feature vectors in input space to the transformed feature vectors in feature space for the better modeling of GMM of source and target features. The quality of statistical modeling is dependent on the distribution and the dimension of data. The proposed method transforms both of the distribution and dimension of data and gives us the chance to model the same data with different configuration. Because the converted feature vectors should be on the input space, only source feature vectors are rearranged in the feature space and target feature vectors remain unchanged for the joint pdf of source and target features using KPCA. The experimental result shows that the proposed method outperforms the conventional GMM-based conversion method in various training environment.