• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.54.3-55
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• 2016

We model the spectral energy distribution (SED) of the Class 0 protostar L1527 IRS using a dust continuum radiative transfer code RADMC-3D to study the initial condition of gravitational collapse. To constrain the envelope structure, we use the data obtained by Herschel /PACS, which covers the far-infrared regime ($55-190{\mu}m$) where the SED of L1527 IRS peaks. According to our modeling, a more flattened density profile fits the far-infrared SED of L1527 IRS better than the density profile of a rotating and infalling envelope. Thus, we employ the density structure of a Bonnor-Ebert sphere, which consists of the inner flat-topped and the outer power-law regions and is often used for describing the density structure of the youngest sources in the low mass star formation process. A Bonnor-Ebert sphere fits very well the observed SED at ${\lambda}$ > $10{\mu}m$, suggesting that L1527 IRS might collapse from an unstable Bonnor-Ebert sphere rather than a singular isothermal sphere.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.1
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• pp.106-111
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• 2016

Thermal noise generated in the electrolyte is modeled for the electrolyte-oxide-semiconductor field-effect transistors. Two noise sources contribute to output noise currents. One is the thermal noise generated in the bulk electrolyte region, and the other is the thermal noise from the double-layer region at the electrolyte-oxide interface. By employing two slightly-different equivalent circuits for two noise current sources, the power spectral density of output noise current is calculated. From the modeling and simulated results, the bulk electrolyte thermal noise dominates the double-layer thermal noise. Electrolyte thermal noise are computed for three different concentrations of NaCl electrolyte. The derived formulas give a good agreement with the published experimental data.

• MALSORI
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• no.67
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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.

• Aerospace Engineering and Technology
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• v.8 no.1
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• pp.17-25
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• 2009

The precise calculation of gas absorption coefficient in the radiative transfer equation is very important to the prediction of radiative heat transfer induced from liquid engine plume in view of base insulation design. For this purpose, the WNB model for gas absorption coefficient is described with the selection of important parameters and then the calculated results are compared with those of SNB model for validation. Total emissivity, narrow band averaged intensity and total intensity are calculated and compared to the results of SNB model. As results, the total emissivity and the total intensity are well matched within 3.1% and roughly 5 % error, respectively. Moreover, the gas modeling database is constructed with estimation of the combustion gas composition of $CO_2$ and $H_2O$ for liquid engine plume.

• Journal of Photoscience
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• v.9 no.2
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• pp.66-69
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• 2002

Zinc chlorin 1 possessing tertiary 3$^1$_hydroxy and 13$^1$-oxo groups was synthesized as a model for the antenna chlorophylls of photosynthetic green bacteria. Self-aggregation of 1 in nonpolar organic solvents was examined and compared to 2 and 3 possessing a secondary and primary 3$^1$_hydroxy group, respectively. Zinc chlorin 1 self-aggregated in I％(v/v) CH$_2$Cl$_2$-hexane to form oligomers and showed a red-shifted Qy maximum at 704 nm compared to the monomer (648 nm in CH$_2$CI2$_2$). This red-shift is larger than that of 3$^1$S-2 (648 to 697 nm) and comparable to that of3$^1$R-2 (648 to 705 nm), but smaller than that of 1 (648 to 740 nm), indicating that while a single 3$^1$-methyl group (primary to secondary OH) suppressed tight and/or extended aggregation, the additional 3$^1$-methyl group (secondary to tertiary OH) did not further suppress aggregation. The relative stability of the aggregates was in the order 3> 3$^1$R-2∼ 1 > 3$^1$S-2 as determined by visible spectral analyses. Molecular modeling calculations on oligomers of zinc chlorins 1, 3$^1$ R-2 and 3 gave similar well-ordered energy-minimized structures, while 3 stacked more tightly than 3$^1$ R- 2 and 1. In contrast, 3$^1$S-2 gave a relatively disordered (twisted) structure. The calculated oligomeric structures could explain the visible spectral data of 1-3 in nonpolar organic solvents. Moreover, self- aggregation of synthetic zinc 13$^1$_oxo-hlorins 4-6 possessing a 2-hydroxyethyl, 3-hydroxypropyl and 3- hydroxy-I-propenyl group at the 3-position in nonpolar organic solvents was discussed.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.3 s.147
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• pp.351-361
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• 2006

The fatigue strength analysis of VLFS is carried out by using a 3-dimensional plate finite element model with a zooming technology which performs the modeling of wide portions of the structure by a coarse mesh but the concerned parts by a very fine mesh of t by t level. And a stepwise substructure modeling technique for global loading conditions is applied which uses the motion response of the global structure from 2-D plate hydroelastic analysis as the enforcing nodal displacements of the concern 3-D structural zooming model. Seven incident wave angles and whole ranges of frequency domains of wave spectrum are considered. In order to consider the effect of breakwater, the modified JONSWAP wave spectrum is used. Applying the wave data of installation region, the longterm spectrum analysis is done based on stochastic process and the fatigue life of the structure is estimated. Finally some design considerations from the view point of fatigue strength analysis of VLFS are discussed.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.59.2-59.2
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• 2020

Disks around protostars are the birthplace of planets. The first step toward planet formation is grain growth from ㎛-sized grains to mm/cm-sized grains in a disk, particularly in dense regions. In order to study whether grains grow and segregate at the protostellar stage, we investigate the ALMA Band 3 (3.1 mm) and 7 (0.87 mm) dust continuum observations of the protostellar disk WL 17 in ρ Ophiuchus L1688 cloud. As reported in a previous study, the Band 3 image shows substructures: a narrow ring and a large central hole. On the other hand, the Band 7 image shows different substructures: a non-axisymmetric ring and an off-center hole. The two-band observations provide a mean spectral index of 2.3, which suggests the presence of mm/cm-sized large grains. Its non-axisymmetric distribution may imply dust segregation between small and large grains. We perform radiative transfer modeling to examine the size and spatial distributions of dust grains in the WL 17 disk. The best-fit model suggests that large grains (>1 cm) exist in the disk, settling down toward the midplane, whereas small grains (~10 ㎛) well mixed with gas are distributed off-center and non-axisymmetrically in a thick layer. The low spectral index and the modeling results suggest that grains rapidly grow at the protostellar stage and that grains differently distribute depending on sizes, resulting in substructures varying with observed wavelengths. To understand the differential grain distributions and substructures, we discuss the effects of the protoplanet(s) expected inside the large hole and the possibility of gravitational instability.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.809-824
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• 2017

The accurate evaluation of wind characteristics and wind-induced structural responses during a typhoon is of significant importance for bridge design and safety assessment. This paper presents an expectation maximization (EM) algorithm-based angular-linear approach for probabilistic modeling of field-measured wind characteristics. The proposed method has been applied to model the wind speed and direction data during typhoons recorded by the structural health monitoring (SHM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. In the summer of 2015, three typhoons, i.e., Typhoon Chan-hom, Typhoon Soudelor and Typhoon Goni, made landfall in the east of China and then struck the Jiubao Bridge. By analyzing the wind monitoring data such as the wind speed and direction measured by three anemometers during typhoons, the wind characteristics during typhoons are derived, including the average wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and power spectral density (PSD). An EM algorithm-based angular-linear modeling approach is proposed for modeling the joint distribution of the wind speed and direction. For the marginal distribution of the wind speed, the finite mixture of two-parameter Weibull distribution is employed, and the finite mixture of von Mises distribution is used to represent the wind direction. The parameters of each distribution model are estimated by use of the EM algorithm, and the optimal model is determined by the values of $R^2$ statistic and the Akaike's information criterion (AIC). The results indicate that the stochastic properties of the wind field around the bridge site during typhoons are effectively characterized by the proposed EM algorithm-based angular-linear modeling approach. The formulated joint distribution of the wind speed and direction can serve as a solid foundation for the purpose of accurately evaluating the typhoon-induced fatigue damage of long-span bridges.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• ETRI Journal
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• v.36 no.5
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• pp.721-729
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• 2014

We propose a novel phase-based method for single-channel speech enhancement to extract and enhance the desired signals in noisy environments by utilizing the phase information. In the method, a phase-dependent a priori signal-to-noise ratio (SNR) is estimated in the log-mel spectral domain to utilize both the magnitude and phase information of input speech signals. The phase-dependent estimator is incorporated into the conventional magnitude-based decision-directed approach that recursively computes the a priori SNR from noisy speech. Additionally, we reduce the performance degradation owing to the one-frame delay of the estimated phase-dependent a priori SNR by using a minimum mean square error (MMSE)-based and maximum a posteriori (MAP)-based estimator. In our speech enhancement experiments, the proposed phase-dependent a priori SNR estimator is shown to improve the output SNR by 2.6 dB for both the MMSE-based and MAP-based estimator cases as compared to a conventional magnitude-based estimator.