• Journal of The Korean Astronomical Society
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• v.49 no.4
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• pp.145-155
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• 2016

The Sausage radio relic is the arc-like radio structure in the cluster CIZA J2242.8+5301, whose observed properties can be best understood by synchrotron emission from relativistic electrons accelerated at a merger-driven shock. However, there remain a few puzzles that cannot be explained by the shock acceleration model with only in-situ injection. In particular, the Mach number inferred from the observed radio spectral index, M_radio ≈ 4.6, while the Mach number estimated from X-ray observations, M_X−ray ≈ 2.7. In an attempt to resolve such a discrepancy, here we consider the re-acceleration model in which a shock of M_s ≈ 3 sweeps through the intracluster gas with a pre-existing population of relativistic electrons. We find that observed brightness profiles at multi frequencies provide strong constraints on the spectral shape of pre-existing electrons. The models with a power-law momentum spectrum with the slope, s ≈ 4.1, and the cutoff Lorentz factor, γ_e,c ≈ 3−5×10⁴, can reproduce reasonably well the observed spatial profiles of radio fluxes and integrated radio spectrum of the Sausage relic. The possible origins of such relativistic electrons in the intracluster medium remain to be investigated further.

• Progress in Superconductivity and Cryogenics
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• v.17 no.4
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• pp.16-20
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• 2015

We investigated optical properties of an electron-doped copper oxide high temperature superconductor, $Pr_{0.85}LaCe_{0.15}CuO_4$ (PLCCO) single crystal. We obtained the optical conductivity from measured reflectance at various temperatures. We found our data contained c-axis longitudinal optical (LO) phonon modes due to miscut and intrinsic lattice distortion. We applied an extended Drude model to study the correlations between charge carriers in the system. The LO phonons appear as strong sharp peaks in the optical scattering rate. We tried to remove the LO phonon modes by using the energy loss function, which also shows the LO phonons as peaks, and could not remove them completely. We extracted the electron-boson spectral density function using a generalized Allen's formula. We observed that the resulting electron-boson density show similar temperature dependence as hole-doped cuprates.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.188-195
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• 2000

This study was conducted to measure the moisture content of powdered food using RF impedance spectroscopic method. In frequency range of 1.0 to 30㎒, the impedance such as reactance and resistance of parallel plate type sample holder filled with wheat flour and red-pepper powder of which moisture content range were 5.93∼-17.07%w.b. and 10.87 ∼ 27.36%w.b., respectively, was characterized using by Q-meter (HP4342). The reactance was a better parameter than the resistance in estimating the moisture density defined as product of moisture content and bulk density which was used to eliminate the effect of bulk density on RF spectral data in this study. Multivariate data analyses such as principal component regression, partial least square regression and multiple linear regression were performed to develop one calibration model having moisture density and reactance spectral data as parameters for determination of moisture content of both wheat flour and red-pepper powder. The best regression model was one by the multiple linear regression model. Its performance for unknown data of powdered food was showed that the bias, standard error of prediction and determination coefficient are 0.179% moisture content, 1.679% moisture content and 0.8849, respectively.

• Wind and Structures
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• v.16 no.5
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• pp.433-455
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• 2013

A phase delay spectrum model towards the representation of spatial coherence of stochastic wind fields is proposed. Different from the classical coherence functions used in the spectral representation methods, the model is derived from the comprehensive description of coherence of fluctuating wind speeds and from the thorough analysis of physical accounts of random factors affecting phase delay, building up a consistent mapping between the simulated fluctuating wind speeds and the basic random variables. It thus includes complete probabilistic information of spatial stochastic wind fields. This treatment prompts a ready and succinct scheme for the simulation of fluctuating wind speeds, and provides a new perspective to the accurate assessment of dynamic reliability of wind-induced structures. Numerical investigations and comparative studies indicate that the developed model is of rationality and of applicability which matches well with the measured data at spatial points of wind fields, whereby the phase spectra at defined datum mark and objective point are feasibly obtained using the numerical scheme associated with the starting-time of phase evolution. In conjunction with the stochastic Fourier amplitude spectrum that we developed previously, the time history of fluctuating wind speeds at any spatial points of wind fields can be readily simulated.

• Smart Structures and Systems
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• v.20 no.6
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• pp.669-682
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• 2017

The normalised version of bispectrum, the so-called bicoherence, has often proved a reliable method of damage detection on engineering applications. Indeed, higher-order spectral analysis (HOSA) has the advantage of being able to detect non-linearity in the structural dynamic response while being insensitive to ambient vibrations. Skewness in the response may be easily spotted and related to damage conditions, as the majority of common faults and cracks shows bilinear effects. The present study tries to extend the application of HOSA to damage localisation, resorting to a neural network based classification algorithm. In order to validate the approach, a non-linear finite element model of a 4-meters-long cantilever beam has been built. This model could be seen as a first generic concept of more complex structural systems, such as aircraft wings, wind turbine blades, etc. The main aim of the study is to train a Neural Network (NN) able to classify different damage locations, when fed with bispectra. These are computed using the dynamic response of the FE nonlinear model to random noise excitation.

• Geomechanics and Engineering
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• v.37 no.6
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• pp.539-554
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• 2024

This study explores development of prediction model for seismic site classification through the integration of machine learning techniques with horizontal-to-vertical spectral ratio (HVSR) methodologies. To improve model accuracy, the research employs outlier detection methods and, synthetic minority over-sampling technique (SMOTE) for data balance, and evaluates using seven machine learning models using seismic data from KiK-net. Notably, light gradient boosting method (LGBM), gradient boosting, and decision tree models exhibit improved performance when coupled with SMOTE, while Multiple linear regression (MLR) and Support vector machine (SVM) models show reduced efficacy. Outlier detection techniques significantly enhance accuracy, particularly for LGBM, gradient boosting, and voting boosting. The ensemble of LGBM with the isolation forest and SMOTE achieves the highest accuracy of 0.91, with LGBM and local outlier factor yielding the highest F1-score of 0.79. Consistently outperforming other models, LGBM proves most efficient for seismic site classification when supported by appropriate preprocessing procedures. These findings show the significance of outlier detection and data balancing for precise seismic soil classification prediction, offering insights and highlighting the potential of machine learning in optimizing site classification accuracy.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.5 s.108
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• pp.408-415
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• 2006

This paper suggests an improved system-level model of RF power amplifiers(PAs) including memory effects, and validates the suggested model by analyzing the power spectral density of the output signal with a predistortion linearizer. The original three-box(Wiener-Hammerstein) model uses input and output filters to capture RF frequency response of PAs. The adjacent spectral regrowth that occurs in three-box model can be perfectly removed by Hammerstein structure predistorter. However, the predistorter based on Hammerstein structure achieves limited performance in real PA applications due to other memory effects except RF frequency response. The spectrum of the output signal can be predicted accurately using the suggested model that changes a memoryless block in a three-box model with a memory polynomial. The proposed model accurately predicts the output spectrum density of PA with Hammerstein structure predistorter with less than 2 dB errors over ${\pm}30$ MHz adjacent channel ranges for IEEE 802.11 g WLAN signal.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2400-2404
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• 2011

Power spectral density (PSD) model of irregularities for the maglev test track is presented. Track irregularities (gauge, cant, twist and vertical) were calculated from the survey data of sleepers on the test track. PSD model was constructed from the estimated PSDs of each track irregularities. Versine (gauge, cant, twist, vertical and lateral) of the track is obtained and their PSDs were estimated, too. Presented PSD model can be used for the analysis of levitation stability and ride quality of the maglev system.

• Journal of The Korean Astronomical Society
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• v.38 no.2
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• pp.267-270
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• 2005

We investigate the spectral energy distributions (SEDs) of low mass-loss rate O-rich asymptotic giant branch (AGB) stars using the infrared observational data including the Infrared Space Observatory (ISO) data. Comparing the results of detailed radiative transfer model calculations with observations, we find that the dust formation temperature is much lower than 1000 K for standard dust shell models. We find that the superwind model with a density-enhanced region can be a possible alternative dust shell model for LMOA stars.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.43.3-43.3
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• 2018

We develop a model for broadband spectral energy distribution (SED) of Pulsar Wind Nebulae (PWNe). The model assumes that electrons/positrons in the pulsar wind are injected into and stochastically accelerated in the pulsar termination shock. We consider two scenarios: a stationary one-zone case and a time-evolving multi-zone case. In the latter scenario, flow properties in the PWNe (magnetic field, bulk speed) are modeled to vary in time and space. We apply the model to the broadband SED of the pulsar wind nebula 3C 58. From the modeling, we find that a broken power-law injection is required with the maximum electron energy of ~200 TeV.