• 제목/요약/키워드: Spectral Distance

검색결과 303건 처리시간 0.024초

Investigation on site conditions for seismic stations in Romania using H/V spectral ratio

  • Pavel, Florin;Vacareanu, Radu
    • Earthquakes and Structures
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    • 제9권5호
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    • pp.983-997
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    • 2015
  • This research evaluates the soil conditions for seismic stations situated in Romania using the horizontal-to-vertical spectral ratio (HVSR). The strong ground motion database assembled for this study consists of 179 analogue and digital strong ground motion recordings from four intermediate-depth Vrancea seismic events with $M_w{\geq}6.0$. In the first step of the analysis, the influence of the earthquake magnitude and source-to-site distance on the H/V curves is evaluated. Significant influences from both the earthquake magnitude and hypocentral distance are found especially for soil class A sites. Next, a site classification method proposed in the literature is applied for each seismic station and the soil classes are compared with those obtained from borehole data and from the topographic slope method. In addition, the success and error rates of this method are computed and compared with other studies from the literature. A more in-depth analysis of the H/V results is performed using data from seismic stations in Bucharest and a comparison of the free-field and borehole H/V curves is done for three seismic stations. The results show large differences between the free-field and the borehole curves. As a conclusion, the results from this study represent an intermediary step in the evaluation of the soil conditions for seismic stations in Romania and the need to perform more detailed soil classification analysis is highly emphasized.

Bayesian approach for the accuracy evaluating of the seismic demand estimation of SMRF

  • Ayoub Mehri Dehno;Hasan Aghabarati;Mehdi Mahdavi Adeli
    • Earthquakes and Structures
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    • 제26권2호
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    • pp.117-130
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    • 2024
  • Probabilistic model of seismic demand is the main tool used for seismic demand estimation, which is a fundamental component of the new performance-based design method. This model seeks to mathematically relate the seismic demand parameter and the ground motion intensity measure. This study is intended to use Bayesian analysis to evaluate the accuracy of the seismic demand estimation of Steel moment resisting frames (SMRFs) through a completely Bayesian method in statistical calculations. In this study, two types of intensity measures (earthquake intensity-related indices such as magnitude and distance and intensity indices related to ground motion and spectral response including peak ground acceleration (PGA) and spectral acceleration (SA)) have been used to form the models. In addition, an extensive database consisting of sixty accelerograms was used for time-series analysis, and the target structures included five SMRFs of three, six, nine, twelve and fifteen stories. The results of this study showed that for low-rise frames, first mode spectral acceleration index is sufficient to accurately estimate demand. However, for high-rise frames, two parameters should be used to increase the accuracy. In addition, adding the product of the square of earthquake magnitude multiplied by distance to the model can significantly increase the accuracy of seismic demand estimation.

무감독 SAM 기법을 이용한 하이퍼스펙트럴 영상 분류 (The Hyperspectral Image Classification with the Unsupervised SAM)

  • 김대성;김진곤;변영기;김용일
    • 한국측량학회:학술대회논문집
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    • 한국측량학회 2004년도 춘계학술발표회논문집
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    • pp.159-164
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    • 2004
  • SAM(Spectral Angle Mapper) is the method using the similarly of the angle between pairs of signatures instead of the spectral distance(MDC, MLC etc.) for classification or clustering. In this paper, we applied unsupervised techniques(Unsupervised SAM and ISODATA) to the Hyperspectral Image(Hyperion) which has innumerable, narrow and contiguous spectral bands and Multispectral Image(ETM$\^$+/) for the clustering of signatures. The overall measured accuracies of the USAM and ISODATA of multispectral image were 76.52%, 53.91% and the USAM and ISODATA of hyperspectral image were 63.04%, 53.91%. From the results of our test, we report that the Unsupervised SAM is better classfication technique than ISODATA. Also we believe that the "Spectral Angle" can potentially be one of the most accurate classifier not only multispectral images but hyperspectral images.

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PROPERTIES AND SPECTRAL BEHAVIOUR OF CLUSTER RADIO HALOS

  • FERETTI L.;BRUNETTI G.;GIOVANNINI G.;KASSIM N.;ORRU E.;SETTI G.
    • 천문학회지
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    • 제37권5호
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    • pp.315-322
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    • 2004
  • Several arguments have been presented in the literature to support the connection between radio halos and cluster mergers. The spectral index distributions of the halos in A665 and A2163 provide a new strong confirmation of this connection, i.e. of the fact that the cluster merger plays an important role in the energy supply to the radio halos. Features of the spectral index (flattening and patches) are indication of a complex shape of the radiating electron spectrum, and are therefore in support of electron reacceleration models. Regions of flatter spectrum are found to be related to the recent merger. In the undisturbed cluster regions, instead, the spectrum steepens with the distance from the cluster center. The plot of the integrated spectral index of a sample of halos versus the cluster temperature indicates that clusters at higher temperature tend to host halos with flatter spectra. This correlation provides further evidence of the connection between radio emission and cluster mergers.

The Endmember Analysis for Sub-Pixel Detection Using the Hyperspectral Image

  • Kim, Dae-Sung;Cho, Young-Wook;Han, Dong-Yeob;Kim, Young-Il
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.732-734
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    • 2003
  • In the middle -resolution remote sensing, the Ground Sampled Distance(GSD) sensed and sampled by the detector is generally larger than the size of objects(or materials) of interest, in which case several objects are embedded in a single pixel and cannot be detected spatially. This study is intended to solve this problem of a hyperspectral data with high spectral resolution. We examined the detection algorithm, Linear Spectral Mixing Model, and also made a test on the Hyperion data. To find class Endmembers, we applied two methods, Spectral Library and Geometric Model, and compared them with each other.

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Realizing the Potential of Small-sized Aperture Camera (SAC) in High-Resolution Imaging Age

  • Choi, Young-Wan;Kim, Ee-Eul;Park, Sung-dong
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.642-644
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    • 2003
  • SAC is a compact electro-optical camera for imaging in visible-NIR spectral ranges. SAC provides highresolution images over the wide geometric and spectral ranges: 10 m ground sample distance (GSD) and 50 km swath width in the spectral ranges of 520 ${\sim}$ 890 nm. SAC is designed to produce high quality images: modulation transfer function (MTF) of more than 15 %; signal-to-noise ratio (SNR) of more than 100. The missions of SAC incorporate various imaging operations: multi-spectral imaging; super swath-width imaging with cameras in parallel; along-track stereo imaging with slanted 2 cameras.

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음성/음악 판별을 위한 특징 파라미터와 분류기의 성능비교 (Performance Comparison of Feature Parameters and Classifiers for Speech/Music Discrimination)

  • 김형순;김수미
    • 대한음성학회지:말소리
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    • 제46호
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    • pp.37-50
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    • 2003
  • In this paper, we evaluate and compare the performance of speech/music discrimination based on various feature parameters and classifiers. As for feature parameters, we consider High Zero Crossing Rate Ratio (HZCRR), Low Short Time Energy Ratio (LSTER), Spectral Flux (SF), Line Spectral Pair (LSP) distance, entropy and dynamism. We also examine three classifiers: k Nearest Neighbor (k-NN), Gaussian Mixure Model (GMM), and Hidden Markov Model (HMM). According to our experiments, LSP distance and phoneme-recognizer-based feature set (entropy and dunamism) show good performance, while performance differences due to different classifiers are not significant. When all the six feature parameters are employed, average speech/music discrimination accuracy up to 96.6% is achieved.

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Effects of blast-induced random ground motions on the stochastic behaviour of industrial masonry chimneys

  • Haciefendioglu, Kemal;Soyluk, Kurtulus
    • Structural Engineering and Mechanics
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    • 제43권6호
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    • pp.835-845
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    • 2012
  • This paper focuses on the stochastic response analysis of industrial masonry chimneys to surface blast-induced random ground motions by using a three dimensional finite element model. Underground blasts induce ground shocks on nearby structures. Depending on the distance between the explosion centre and the structure, masonry structures will be subjected to ground motions due to the surface explosions. Blast-induced random ground motions can be defined in terms of the power spectral density function and applied to each support point of the 3D finite element model of the industrial masonry system. In this paper, mainly a parametric study is conducted to estimate the effect of the blast-induced ground motions on the stochastic response of a chimney type masonry structure. With this purpose, different values of charge weight and distance from the charge centre are considered for the analyses of the chimney. The results of the study underline the remarkable effect of the surface blast-induced ground motions on the stochastic behaviour of industrial masonry type chimneys.

인삼선별의 자동화를 위한 컴퓨터 시각장치 - 등급 자동판정을 위한 영상처리 알고리즘 개발 - (Computer Vision System for Automatic Grading of Ginseng - Development of Image Processing Algorithms -)

  • 김철수;이중용
    • Journal of Biosystems Engineering
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    • 제22권2호
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    • pp.227-236
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    • 1997
  • Manual grading and sorting of red-ginsengs are inherently unreliable due to its subjective nature. A computerized technique based on optical and geometrical characteristics was studied for the objective quality evalution. Spectral reflectance of three categories of red-ginsengs - "Chunsam", "Chisam", "Yangsam" - were measured and analyzed. Variation of reflectance among parts of a single ginseng was more significant than variation among the quality categories of ginsengs. A PC-based image processing algorithm was developed to extract geometrical features such as length and thickness of body, length and number of roots, position of head and branch point, etc. The algorithm consisted of image segmentation, calculation of Euclidean distance, skeletonization and feature extraction. Performance of the algorithm was evaluated using sample ginseng images and found to be mostly sussessful.

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Filtering of Filter-Bank Energies for Robust Speech Recognition

  • Jung, Ho-Young
    • ETRI Journal
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    • 제26권3호
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    • pp.273-276
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    • 2004
  • We propose a novel feature processing technique which can provide a cepstral liftering effect in the log-spectral domain. Cepstral liftering aims at the equalization of variance of cepstral coefficients for the distance-based speech recognizer, and as a result, provides the robustness for additive noise and speaker variability. However, in the popular hidden Markov model based framework, cepstral liftering has no effect in recognition performance. We derive a filtering method in log-spectral domain corresponding to the cepstral liftering. The proposed method performs a high-pass filtering based on the decorrelation of filter-bank energies. We show that in noisy speech recognition, the proposed method reduces the error rate by 52.7% to conventional feature.

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