• 제목/요약/키워드: background component

검색결과 600건 처리시간 0.025초

Laver Farm Feature Extraction From Landsat ETM+ Using Independent Component Analysis

  • Han J. G.;Yeon Y. K.;Chi K. H.;Hwang J. H.
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.359-362
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    • 2004
  • In multi-dimensional image, ICA-based feature extraction algorithm, which is proposed in this paper, is for the purpose of detecting target feature about pixel assumed as a linear mixed spectrum sphere, which is consisted of each different type of material object (target feature and background feature) in spectrum sphere of reflectance of each pixel. Landsat ETM+ satellite image is consisted of multi-dimensional data structure and, there is target feature, which is purposed to extract and various background image is mixed. In this paper, in order to eliminate background features (tidal flat, seawater and etc) around target feature (laver farm) effectively, pixel spectrum sphere of target feature is projected onto the orthogonal spectrum sphere of background feature. The rest amount of spectrum sphere of target feature in the pixel can be presumed to remove spectrum sphere of background feature. In order to make sure the excellence of feature extraction method based on ICA, which is proposed in this paper, laver farm feature extraction from Landsat ETM+ satellite image is applied. Also, In the side of feature extraction accuracy and the noise level, which is still remaining not to remove after feature extraction, we have conducted a comparing test with traditionally most popular method, maximum-likelihood. As a consequence, the proposed method from this paper can effectively eliminate background features around mixed spectrum sphere to extract target feature. So, we found that it had excellent detection efficiency.

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Wind-induced responses and equivalent static wind loads of tower-blade coupled large wind turbine system

  • Ke, S.T.;Wang, T.G.;Ge, Y.J.;Tamura, Y.
    • Structural Engineering and Mechanics
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    • 제52권3호
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    • pp.485-505
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    • 2014
  • This study aimed to develop an approach to accurately predict the wind models and wind effects of large wind turbines. The wind-induced vibration characteristics of a 5 MW tower-blade coupled wind turbine system have been investigated in this paper. First, the blade-tower integration model was established, which included blades, nacelle, tower and the base of the wind turbine system. The harmonic superposition method and modified blade element momentum theory were then applied to simulate the fluctuating wind field for the rotor blades and tower. Finally, wind-induced responses and equivalent static wind loads (ESWL) of the system were studied based on the modified consistent coupling method, which took into account coupling effects of resonant modes, cross terms of resonant and background responses. Furthermore, useful suggestions were proposed to instruct the wind resistance design of large wind turbines. Based on obtained results, it is shown from the obtained results that wind-induced responses and ESWL were characterized with complicated modal responses, multi-mode coupling effects, and multiple equivalent objectives. Compared with the background component, the resonant component made more contribution to wind-induced responses and equivalent static wind loads at the middle-upper part of the tower and blades, and cross terms between background and resonant components affected the total fluctuation responses, while the background responses were similar with the resonant responses at the bottom of tower.

Telephone Speech Recognition with Data-Driven Selective Temporal Filtering based on Principal Component Analysis

  • Jung Sun Gyun;Son Jong Mok;Bae Keun Sung
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2004년도 학술대회지
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    • pp.764-767
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    • 2004
  • The performance of a speech recognition system is generally degraded in telephone environment because of distortions caused by background noise and various channel characteristics. In this paper, data-driven temporal filters are investigated to improve the performance of a specific recognition task such as telephone speech. Three different temporal filtering methods are presented with recognition results for Korean connected-digit telephone speech. Filter coefficients are derived from the cepstral domain feature vectors using the principal component analysis.

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Dynamic characteristics of transmission line conductors and behaviour under turbulent downburst loading

  • Darwish, Mohamed M.;El Damatty, Ashraf A.;Hangan, Horia
    • Wind and Structures
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    • 제13권4호
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    • pp.327-346
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    • 2010
  • During the past decade, many electrical transmission tower structures have failed during downburst events. This study is a part of a research program aimed to understand the behaviour of transmission lines under such localized wind events. The present study focuses on the assessment of the dynamic behaviour of the line conductors under downburst loading. A non-linear numerical model, accounting for large deformations and the effect of pretension loading, is developed and used to predict the natural frequencies and mode shapes of conductors at various loading stages. A turbulence signal is extracted from a set of full-scale data. It is added to the mean component of the downburst wind field previously evaluated from a CFD analysis. Dynamic analysis is performed using various downburst configurations. The study reveals that the response is affected by the background component, while the resonant component turns to be negligible due large aerodynamic damping of the conductors.

신경회로망을 이용한 ECG 특성점 검출에 관한 연구 (A Study on Detection of Significant point in ECG using Neural Network)

  • 손상윤;정기삼;정성진;이명호
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1995년도 추계학술대회
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    • pp.109-112
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    • 1995
  • This paper is a study on the detection of the significant point in ECG signal. ECG signal consists of two components; one is high frequency component to be detected and the other is low frequency component to be removed. AR model is appropriate for modelling and removing the low frequency component. AR model coefficients are updated by artificial neural network algorithm. We can remove the background noise(low frequency) by passing through the AR filter. The remaining signals which include high frequency noise are sent to the matched filter to pass only the signal which we want to extract. The template used in matched filter is updated adaptively.

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폐에 발생한 암육종의 세침흡인 세포학적소견 -1 증례보고- (Fine Needle Aspiration Cytology of Pulmonary Carcinosarcoma)

  • 장태정;이광길;홍순원
    • 대한세포병리학회지
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    • 제1권2호
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    • pp.164-169
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    • 1990
  • Carcinsarcoma is an uncommon pulmonary malignancy characterized by carcinmatous parenchyma and sarcomatous stroma. The cytologic, immunohistochemical and ultrastructural features of a case of pulmonary carcinosarcoma suspected by fine needle aspiration cytology is presented. Only bizarre spindle cells arranged in loose groups, in microtissue fragments and in a dissociate fashion were present on the aspiration smears. They were markedly positive for vimentin. The epithelial component was not found, which was probably due to marked paucity of carcinomatous component that was proved by histologic examination of the resected tumor. The diagnosis of pulmonary carcinosarcoma should be conidered whenever poorly differentiated epithelial ceil groups with a malignant mesenchymal component set in a myxoid background are seen in a pulmonary cytology specimen.

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텍스처 정보 기반의 PCA를 이용한 문서 영상의 분석 (Texture-based PCA for Analyzing Document Image)

  • 김보람;김욱현
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2006년도 하계종합학술대회
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    • pp.283-284
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    • 2006
  • In this paper, we propose a novel segmentation and classification method using texture features for the document image. First, we extract the local entropy and then segment the document image to separate the background and the foreground using the Otsu's method. Finally, we classify the segmented regions into each component using PCA(principle component analysis) algorithm based on the texture features that are extracted from the co-occurrence matrix for the entropy image. The entropy-based segmentation is robust to not only noise and the change of light, but also skew and rotation. Texture features are not restricted from any form of the document image and have a superior discrimination for each component. In addition, PCA algorithm used for the classifier can classify the components more robustly than neural network.

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Eigen-background와 Clustering을 이용한 객체 검출 시스템 (An Object Detection System using Eigen-background and Clustering)

  • 전재덕;이미정;김종호;김상균;강병두
    • 한국멀티미디어학회논문지
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    • 제13권1호
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    • pp.47-57
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    • 2010
  • 객체 검출은 영상에서 객체의 식별, 위치정보, 상황인식 등을 위해서 필수적이다. 본 논문에서는 강인한 객체 검출 시스템을 제안한다. Principal Component Analysis (PCA)를 이용하여 배경 영상에서 수집한 학습데이터를 주성분으로 선형변환 한다. 객체와 배경에 대하여 판별 능력이 우수한 주성분을 선별하여 Eigen-background를 구성한다. Fuzzy-C-Means (FCM)은 Eigen-background의 정보를 입력 차원으로 하여 영상을 Clustering하고 객체와 배경으로 분류한다. 고정된 카메라에서 배경변화에 적용 가능한 시스템을 구현하기 위해 동일한 시점에서 움직이는 객체가 포함된 영상을 학습데이터로 사용하였다. 제안하는 시스템은 인위적인 한 프레임을 배경으로 정의하여 사용하는 과정이 필요 없이 입력 영상에서 잡음이 제거된 객체와 배경으로 분류하였고, 또한 객체의 부분적인 움직임도 효과적으로 검출하였다.

Full spectrum estimation of helicopter background and cosmic gamma-ray contribution for airborne measurements

  • Lukas Kotik;Marcel Ohera
    • Nuclear Engineering and Technology
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    • 제55권3호
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    • pp.1052-1060
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    • 2023
  • The airborne radiation monitoring has been used in geophysics for more than forty years and now it also has its important role in emergency monitoring. The aircraft background and the cosmic gamma-rays contribute to the measured gamma spectrum on the aircraft board. This adverse effect should be eliminated before the data processing. The paper describes two semiparametric methods to estimate the full spectrum aircraft background and cosmic gamma-ray contribution from spectra measured at altitudes where terrestrial contribution is negligible. The methods only assume to know possible peak positions in spectra and their full width at half maximum, that can be easily obtained e.g. from terrestrial measurement. The methods were applied to real experimental data acquired on Mi-17 and Bell 412 helicopter boards. The IRIS airborne gamma-ray spectrometer, with 4×4 L NaI(Tl) crystals, produced by Pico Envirotec Inc., Canada, was used on helicopters' boards. To obtain valid estimate of the aircraft background and the cosmic contribution, the measurements over sea and large water areas were carried out. However, the satisfactory results over inland were also achieved comparing with those acquired over large water areas.

Monotonic and Parallelizable Algorithm for Simultaneous Reconstruction of Activity/Attenuation using Emission data in PET

  • Kim, Seung-Gu
    • Communications for Statistical Applications and Methods
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    • 제8권1호
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    • pp.299-309
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    • 2001
  • In PET(Positron Emission Tomography), it is necessary to use transmission scan data in order to estimate the attenuation map. Recently, there are several empirical studies in which one might be able to estimate attenuation map and activity distribution simultaneously with emissive sinogram alone without transmission scan. However, their algorithms are based on the model in which does not include the background counts term, and so is unrealistic. If the background counts component has been included in the model, their algorithm would introduce non-monotonic reconstruction algorithm which results in vain in practice. in this paper, we develop a monotonic and parallelizable algorithm for simultaneous reconstruction of both characteristics and present the validity through some simulations.

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