• Title/Summary/Keyword: Spectral Distribution

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Estimation of Spectral Radiant Distribution of Illumination and Corresponding Color Reproduction According to Viewing Conditions (광원의 분광 방사 분포의 추정과 관찰조건에 따른 대응적 색재현)

  • 방상택;이철희;곽한봉;유미옥;안석출
    • Proceedings of the Korean Printing Society Conference
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    • 2000.04a
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    • pp.35-44
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    • 2000
  • Because Image on the CRT change under different illuminants, human is difficult to see original color of object. If what is information of used illuminant on capturing object know, image can be transformed according to viewing condition using the linear matrix method. To know information of used illuminant at an image, the spectral radiance of illuminant can be estimated using the linear model of Maloney and Wandell form an image. And then image can be properly transformed it using color appearance model. In this paper, we predict the spectral radiance of illuminant using spectral power distribution of specular light and using surface spectral reflectance at maximum gray area. and then we perform visual experiments for the corresponding color reproduction according to viewing condition. In results, we ensure that the spectral radiance of illuminant at an image can be well estimated using above algorithms and that human visual system is 70% adapted to the monitor's white point and 30% to ambient light when viewing softcopy images.

Probabilistic analysis of spectral displacement by NSA and NDA

  • Devandiran, P.;Kamatchi, P.;Rao, K. Balaji;Ravisankar, K.;Iyer, Nagesh R.
    • Earthquakes and Structures
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    • v.5 no.4
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    • pp.439-459
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    • 2013
  • Main objective of the present study is to determine the statistical properties and suitable probability distribution functions of spectral displacements from nonlinear static and nonlinear dynamic analysis within the frame work of Monte Carlo simulation for typical low rise and high rise RC framed buildings located in zone III and zone V and designed as per Indian seismic codes. Probabilistic analysis of spectral displacement is useful for strength assessment and loss estimation. To the author's knowledge, no study is reported in literature on comparison of spectral displacement including the uncertainties in capacity and demand in Indian context. In the present study, uncertainties in capacity of the building is modeled by choosing cross sectional dimensions of beams and columns, density and compressive strength of concrete, yield strength and elastic modulus of steel and, live load as random variables. Uncertainty in demand is modeled by choosing peak ground acceleration (PGA) as a random variable. Nonlinear static analysis (NSA) and nonlinear dynamic analysis (NDA) are carried out for typical low rise and high rise reinforced concrete framed buildings using IDARC 2D computer program with the random sample input parameters. Statistical properties are obtained for spectral displacements corresponding to performance point from NSA and maximum absolute roof displacement from NDA and suitable probability distribution functions viz., normal, Weibull, lognormal are examined for goodness-of-fit. From the hypothesis test for goodness-of-fit, lognormal function is found to be suitable to represent the statistical variation of spectral displacement obtained from NSA and NDA.

Integrating physics-based fragility for hierarchical spectral clustering for resilience assessment of power distribution systems under extreme winds

  • Jintao Zhang;Wei Zhang;William Hughes;Amvrossios C. Bagtzoglou
    • Wind and Structures
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    • v.39 no.1
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    • pp.1-14
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    • 2024
  • Widespread damages from extreme winds have attracted lots of attentions of the resilience assessment of power distribution systems. With many related environmental parameters as well as numerous power infrastructure components, such as poles and wires, the increased challenge of power asset management before, during and after extreme events have to be addressed to prevent possible cascading failures in the power distribution system. Many extreme winds from weather events, such as hurricanes, generate widespread damages in multiple areas such as the economy, social security, and infrastructure management. The livelihoods of residents in the impaired areas are devastated largely due to the paucity of vital utilities, such as electricity. To address the challenge of power grid asset management, power system clustering is needed to partition a complex power system into several stable clusters to prevent the cascading failure from happening. Traditionally, system clustering uses the Binary Decision Diagram (BDD) to derive the clustering result, which is time-consuming and inefficient. Meanwhile, the previous studies considering the weather hazards did not include any detailed weather-related meteorologic parameters which is not appropriate as the heterogeneity of the parameters could largely affect the system performance. Therefore, a fragility-based network hierarchical spectral clustering method is proposed. In the present paper, the fragility curve and surfaces for a power distribution subsystem are obtained first. The fragility of the subsystem under typical failure mechanisms is calculated as a function of wind speed and pole characteristic dimension (diameter or span length). Secondly, the proposed fragility-based hierarchical spectral clustering method (F-HSC) integrates the physics-based fragility analysis into Hierarchical Spectral Clustering (HSC) technique from graph theory to achieve the clustering result for the power distribution system under extreme weather events. From the results of vulnerability analysis, it could be seen that the system performance after clustering is better than before clustering. With the F-HSC method, the impact of the extreme weather events could be considered with topology to cluster different power distribution systems to prevent the system from experiencing power blackouts.

ATSC Digital Television Signal Detection with Spectral Correlation Density

  • Yoo, Do-Sik;Lim, Jongtae;Kang, Min-Hong
    • Journal of Communications and Networks
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    • v.16 no.6
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    • pp.600-612
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    • 2014
  • In this paper, we consider the problem of spectrum sensing for advanced television systems committee (ATSC) digital television (DTV) signal detection. To exploit the cyclostationarity of the ATSC DTV signals, we employ spectral correlation density (SCD) as the decision statistic and propose an optimal detection algorithm. The major difficulty is in obtaining the probability distribution functions of the SCD. To overcome the difficulty, we probabilistically model the pilot frequency location and employ Gaussian approximation for the SCD distribution. Then, we obtain a practically implementable detection algorithm that outperforms the industry leading systems by 2-3 dB. We also propose various techniques that greatly reduce the system complexity with performance degradation by only a few tenths of decibels. Finally, we show how robust the system is to the estimation errors of the noise power spectral density level and the probability distribution of the pilot frequency location.

ANOTHER COMPLETE DECOMPOSITION OF A SELF-SIMILAR CANTOR SET

  • Baek, In Soo
    • Korean Journal of Mathematics
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    • v.16 no.2
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    • pp.157-163
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    • 2008
  • Using informations of subsets of divergence points and the relation between members of spectral classes, we give another complete decomposition of spectral classes generated by lower(upper) local dimensions of a self-similar measure on a self-similar Cantor set with full information of their dimensions. We note that it is a complete refinement of the earlier complete decomposition of the spectral classes. Further we study the packing dimension of some uncountable union of distribution sets.

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THE CONTINUOUS DENSITY FUNCTION OF THE LIMITING SPECTRAL DISTRIBUTION

  • Choi, Sang-Il
    • Journal of applied mathematics & informatics
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    • v.28 no.1_2
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    • pp.515-521
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    • 2010
  • In multivariate analysis, the inversion formula of the Stieltjes transform is used to find the density of a spectral distribution of random matrices of sample covariance type. Let $B_n\;=\;\frac{1}{N}Y_nY_n^TT_n$ where $Y_n\;=\;[Y_{ij}]_{n\;{\times}\;N}$ is with independent, identically distributed entries and $T_n$ is an $n\;{\times}\;n$ symmetric non-negative definite random matrix independent of the $Y_{ij}$'s. In the present paper, using the inversion formula of the Stieltjes transform, we will find that the limiting distribution of $B_n$ has a continuous density function away from zero.

THE INVERSION FORMULA OF THE STIELTJES TRANSFORM OF SPECTRAL DISTRIBUTION

  • Choi, Sang-Il
    • Journal of the Chungcheong Mathematical Society
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    • v.22 no.3
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    • pp.519-524
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    • 2009
  • In multivariate analysis, the inversion formula of the Stieltjes transform is used to find the density of a spectral distribution of random matrices of sample covariance type. Let $B_{n}\;=\;\frac{1}{n}Y_{m}^{T}T_{m}Y_{m}$ where $Ym\;=\;[Y_{ij}]_{m{\times}n}$ is with independent, identically distributed entries and $T_m$ is an $m{\times}m$ symmetric nonnegative definite random matrix independent of the $Y_{ij}{^{\prime}}s$. In the present paper, using the inversion formula of the Stieltjes transform, we will find the density function of the limiting distribution of $B_n$ away from zero.

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Detection of Ecosystem Distribution Plants using Drone Hyperspectral Spectrum and Spectral Angle Mapper (드론 초분광 스펙트럼과 분광각매퍼를 적용한 생태계교란식물 탐지)

  • Kim, Yong-Suk
    • Journal of Environmental Science International
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    • v.30 no.2
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    • pp.173-184
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    • 2021
  • Ecological disturbance plants distributed throughout the country are causing a lot of damage to us directly or indirectly in terms of ecology, economy and health. These plants are not easy to manage and remove because they have a strong fertility, and it is very difficult to express them quantitatively. In this study, drone hyperspectral sensor data and Field spectroradiometer were acquired around the experimental area. In order to secure the quality accuracy of the drone hyperspectral image, GPS survey was performed, and a location accuracy of about 17cm was secured. Spectroscopic libraries were constructed for 7 kinds of plants in the experimental area using a Field spectroradiometer, and drone hyperspectral sensors were acquired in August and October, respectively. Spectral data for each plant were calculated from the acquired hyperspectral data, and spectral angles of 0.08 to 0.36 were derived. In most cases, good values of less than 0.5 were obtained, and Ambrosia trifida and Lactuca scariola, which are common in the experimental area, were extracted. As a result, it was found that about 29.6% of Ambrosia trifida and 31.5% of Lactuca scariola spread in October than in August. In the future, it is expected that better results can be obtained for the detection of ecosystem distribution plants if standardized indicators are calculated by constructing a precise spectral angle standard library based on more data.

Development of Empirical Formulas for Approximate Spectral Moment Based on Rain-Flow Counting Stress-Range Distribution

  • Jun, Seockhee;Park, Jun-Bum
    • Journal of Ocean Engineering and Technology
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    • v.35 no.4
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    • pp.257-265
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    • 2021
  • Many studies have been performed to predict a reliable and accurate stress-range distribution and fatigue damage regarding the Gaussian wide-band stress response due to multi-peak waves and multiple dynamic loads. So far, most of the approximation models provide slightly inaccurate results in comparison with the rain-flow counting method as an exact solution. A step-by-step study was carried out to develop new approximate spectral moments that are close to the rain-flow counting moment, which can be used for the development of a fatigue damage model. Using the special parameters and bandwidth parameters, four kinds of parameter-based combinations were constructed and estimated using the R-squared values from regression analysis. Based on the results, four candidate empirical formulas were determined and compared with the rain-flow counting moment, probability density function, and root mean square (RMS) value for relative distance. The new approximate spectral moments were finally decided through comparison studies of eight response spectra. The new spectral moments presented in this study could play an important role in improving the accuracy of fatigue damage model development. The present study shows that the new approximate moment is a very important variable for the enhancement of Gaussian wide-band fatigue damage assessment.

Spectral Distribution and Spectral Absorption of Suspended particulates in Waters of Sanya Bay

  • Yang, Dingtian;Cao, Wenxi
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.495-498
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    • 2006
  • Optical profile and spectral absorption of suspended solids in waters of Sanya bay was measured on August 8-14, 2003. Optical profile was taken by using MicroPro optical profile. Apparent optical indexes, vertical diffuse attenuation coefficient ($K_d$) and water leaving radiance (Lw), were calculated. $K_d$ at the blue end of the spectrum was greater than that at the red end of the spectrum in waters near Sanya River mouth, however, in waters near open sea, $K_d$ at the blue end of the spectrum was smaller than that at the red end of the spectrum. Distribution of water leaving radiance was relatively higher in waters near Sanya River mouth, but relatively weaker in near open sea water. Spectral absorption of suspended particulates was also measured. Results showed that the spectral absorption of chlorophyll a was greater in waters near Sanya river mouth, but relatively weaker in waters near open sea, which indicated higher concentration of phytoplankton in waters near Sanya river mouth. Except for water at the 5th sampling station, the ratio of spectral absorption of chlorophyll a to total suspended particulates in surface waters was greater than that in bottom waters at all stations.

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