• Structural Monitoring and Maintenance
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• 제9권2호
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• pp.179-200
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• 2022

This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T² and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.

• 한국초전도ㆍ저온공학회논문지
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• 제26권2호
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• pp.1-4
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• 2024

We investigated Pb_10-xCu_x(PO₄)₆ (0.9 < x < 1.1) (LK-99) and Cu₂S, presumed to be contained as an impurity in LK-99, in a wide spectral range from far infrared to ultraviolet using optical spectroscopy. The optical conductivity spectra of both samples were obtained from measured reflectance spectra at various temperatures from 80 to 434 K. Both samples showed several infrared-active phonons in the far and mid-infrared regions. LK-99 showed typical insulating features with a band gap of ~1 eV. Cu₂S showed a nonmonotonic temperature-dependent trend and two energy gaps: one energy gap of ~93 meV and a band gap of 2.42 eV. Our results indicate that LK-99 cannot be a superconductor because it is an insulator with a large band gap.

• 한국정보통신학회논문지
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• 제7권4호
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• pp.598-603
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• 2003

본 논문에서는 주파수 부대역마다 최적의 특징추출을 위해서, 음성인식률을 기준으로 최적의 방법을 선택한다. 다중대역 음성인식 접근을 사용하여 각기 다른 주파수 영역에서 특징벡터를 독립적으로 추출함으로써 부대역별로 다른 특징추출 방법을 적용할 수 있었다. 저주파 대역의 음성은 비교적 스펙트럼의 구조가 명확하므로 전극모델을 사용하는 것이 효과적이었고, 고주파 대역에서는 비모수적인 변환방법인 이산 코사인 변환을 사용한 켑스트럼이 효과적이었다. 부대역별로 효과적인 특징추출 방법을 사용함으로써, 각 주파수 부대역에 포함된 음성인식을 위한 언어정보를 보다 효과적으로 추출할 수 있었다. 음성인식 실험결과, 제안한 방법은 전대역 특징추출보다 우수한 성능을 나타내었다.

• 한국컴퓨터정보학회논문지
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• 제17권8호
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• pp.91-97
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• 2012

본 논문에서는 각 프레임에서의 음성신호 및 비음성신호 구간을 검출하는 음성인식 알고리즘을 제안한다. 그리고 음성신호 및 비음성신호 구간의 검출에 따라서 각 프레임에서 잡음을 제거하는 멀티밴드필터에 의한 환경잡음억압 알고리즘을 제안한다. 이 알고리즘은 음성으로부터 특징 파라미터를 추출하여 필터뱅크의 서브밴드 영역에서 잡음을 제거하는 방법이다. 본 실험에서는 환경잡음억압 알고리즘의 성능을 멀티밴드필터를 사용하여 각 프레임에서 잡음을 제거하는 실험결과를 나타낸다. 잡음에 의하여 오염된 음성에 대하여 스펙트럴 왜곡률을 사용하여 본 알고리즘이 유효하다는 것을 확인한다.

• 천문학회보
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• 제44권2호
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• pp.49.2-49.2
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• 2019

We present results from our long-term observing campaign, using the NASA IRTF at Maunakea, to obtain 2 - 4 ㎛ spectra of 118 red point sources in the line of sight to the Galactic Center (GC). Our sample is largely composed of point sources selected from near- and mid-infrared photometry, but also includes a number of massive young stellar objects. Many of these sources show high foreground extinction as shown by deep 3.4 ㎛ aliphatic hydrocarbon absorption feature, which is a characteristic of the diffuse ISM and comes from the long line of sight through the diffuse medium toward the Central Molecular Zone (CMZ), the central 300 pc region of the GC. The deep 3.1 ㎛ H₂O ice absorption band coming from the local, dense material in the GC CMZ suggests that most sources are likely located in the GC CMZ. A few of these sources show weak CCH₃OH ice absorption at 3.535 ㎛, which can provide a strong constraint on the CCH₃OH ice formation in the unique environment of the CMZ. From the best-fitting models, the optical depths of these features are determined and used to generate a well-rounded view of the ice composition across the GC CMZ and the spectral characteristics of massive YSOs in the GC.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.25-28
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• 2006

We propose a new method of masking cloud-affected pixels in satellite ocean color imageries such as of GLI. Those pixels, mostly found around cloud pixels or in scattered cloud area, have anomalous features in either in chlorophyll-a estimate or in water reflectance. This artifact is most likely caused by residual error of inter-band registration correction. Our method is to check the pixel-wise 'soundness' of the spectral water reflectance Rw retrieved after the atmospheric correction. First, we define two spectral ratio between water reflectance, IRR1 and IRR2, each defined as RW(B1)/RW (B3) RW (B3) and as RW (B2)/RW(B4) respectively, where $B1{\sim}B4$ stand for 4 consecutive visible bands. We show that an almost linear relation holds over log-scaled IRR1 and IRR2 for shipmeasured RW data of SeaBAM in situ data set and for GLI cloud-free Level 2 sub-scenes. The method we propose is to utilize this nature, identifying those pixels that show significant discrepancy from that relationship. We apply this method to ADEOS-II/GLI ocean color data to evaluate the performance over Level-2 data, which includes different water types such as case 1, turbid case 2 and coccolithophore bloom waters.

• International Journal of Oral Biology
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• 제46권3호
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• pp.105-110
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• 2021

The physicochemical properties of crystalline titanium dioxide nanoparticles (TiO₂ NPs) were investigated by comparing amorphous (amTiO₂), anatase (aTiO₂), metaphase of anatase-rutile (arTiO₂), and rutile (rTiO₂) NPs, which were prepared at various calcination temperatures (100℃, 400℃, 600℃, and 900℃). X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses confirmed that the phase-transformed TiO₂ had the characteristic features of crystallinity and average size. The surface chemical properties of the crystalline phases were different in the spectral analysis. As anatase transformed to the rutile phase, the band of the hydroxyl group at 3,600-3,100 cm^-1 decreased gradually, as assessed using Fourier transform infrared spectroscopy (FT-IR). For ultraviolet-visible (UV-Vis) spectra, the maximum absorbance of anatase TiO₂ NPs at 309 nm was blue-shifted to 290 nm at the rutile phase with reduced absorbance. Under the electric field of capillary electrophoresis (CE), TiO₂ NPs in anatase migrated and detected as a broaden peak, whereas the rutile NPs did not. In addition, anatase showed the highest photocatalytic activity in an UV-irradiated dye degradation assay in the following order: aTiO₂ > arTiO₂ > rTiO₂. Overall, the phases of TiO₂ NPs showed characteristic physicochemical properties regarding size, surface chemical properties, UV absorbance, CE migration, and photocatalytic activity.

• 한국음향학회지
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• 제42권6호
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• pp.603-616
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• 2023

본 연구는 주파수 및 시간 특성을 활용하여 머신러닝 기반 공동주택 주거소음의 군집화 및 분류를 진행하였다. 먼저, 공동주택 주거소음의 군집화 및 분류를 진행하기 위하여 주거소음원 데이터셋을 구축하였다. 주거소음원 데이터셋은 바닥충격음, 공기전달음, 급배수 및 설비소음, 환경소음, 공사장 소음으로 구성되었다. 각 음원의 주파수 특성은 1/1과 1/3 옥타브 밴드별 L_eq와 L_max값을 도출하였으며, 시간적 특성은 5 s 동안의 6 ms 간격의 음압레벨 분석을 통해 L_eq값을 도출하였다. 공동주택 주거소음원의 군집화는 K-Means clustering을 통해 진행하였다. K-Means의 k의 개수는 실루엣 계수와 엘보우 방법을 통해 결정하였다. 주파수 특성을 통한 주거소음원 군집화는 모든 평가지수에서 3개로 군집되었다. 주파수 특성 기준으로 분류된 각 군집별 시간적 특성을 통한 주거소음원 군집화는 L_eq평가지수의 경우 9개, L_max 경우는 11개로 군집되었다. 주파수 특성을 통해 군집된 각 군집은 타 주파수 대역 대비 저주파 대역의 음에너지의 비율 또한 조사되었다. 이후, 군집화 결과를 활용하기 위한 방안으로 세 종류의 머신러닝 방법을 이용해 주거소음을 분류하였다. 주거소음 분류 결과, 1/3 옥타브 밴드의 L_eq값으로 라벨링된 데이터에서 가장 높은 정확도와 f1-score가 나타났다. 또한, 주파수 및 시간적 특성을 모두 사용하여 인공신경망(Artificial Neural Network, ANN) 모델로 주거소음원을 분류했을 때 93 %의 정확도와 92 %의 f1-score로 가장 높게 나타났다.