• Journal of Multimedia Information System
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• v.8 no.2
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• pp.93-100
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• 2021

Under the time-varying temperature, the high-temperature radiation of forgings and the change of reflection characteristics of oxide skin on the surface of forgings lead to the difficulty of obtaining images to truly reflect the geometric characteristics of forgings. It is urgent to study the clear and reliable acquisition method of hot forging feature image under time-varying temperature to meet the requirements of visual measurement of hot geometric parameters of forgings. Based on this, this chapter first puts forward the quality evaluation method of forging feature image, which provides guarantee for the accurate evaluation of feature image quality. Furthermore, the factors that affect the image quality, such as the radiation characteristics of forgings and the photographic characteristics of cameras, are analyzed, and the imaging spectrum which can effectively suppress the radiation intensity of forgings is determined. Finally, aiming at the problem that the quality of image acquisition is difficult to guarantee due to the drastic change of radiation intensity of forgings under time-varying temperature, an image acquisition method based on minimum signal-to-noise ratio (SNR) based laser light intensity adaptation is proposed, which significantly improves the definition of feature light strips in forging images at high temperature, and finally realizes the clear acquisition of feature images of large-scale hot forging under time-varying temperature.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1712-1725
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• 2022

For improving the seismic performance of the nuclear power plant (NPP) piping system, attempts have been made to apply a dynamic absorber (DA). However, the current piping DA design method is limited because it cannot provide the globally optimum values for the target design seismic loading. Therefore, this study proposes a seismic time history analysis-based DA optimal design method for piping. To this end, the Kriging approach is introduced to reduce the numerical cost required for seismic time history analyses. The appropriate design of the experiment method is used to increase the efficiency in securing response data. A gradient-based method is used to efficiently deal with the multi-dimensional unconstrained optimization problem of the DA optimal design. As a result, the proposed method showed an excellent response reduction effect in several responses compared to other optimal design methods. The proposed method showed that the average response reduction rate was about 9% less at the maximum acceleration, about 5% less at the maximum value of the response spectrum, about 9% less at the maximum relative displacement, and about 4% less at the maximum combined stress compared to existing optimal design methods. Therefore, the proposed method enables an effective optimal DA design method for mitigating seismic response in NPP piping in the future.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4226-4230
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• 2022

The Korea Atomic Energy Research Institute (KAERI) has designed a Hybrid-Low Power Research Reactor (H-LPRR) which can be used for critical assembly and conventional research reactor as well. It is an open tank-in-pool type research reactor (Thermal Power: 50 kW_th) of which the most important applications are Neutron Activation Analysis (NAA), Radioisotope (RI) production, education and training. There are eight irradiation holes on the edge of the reactor core: IR (6 holes for RI production) and NA (2 holes for NAA) holes. In order to quantify the elemental concentration in target samples through the Instrumental Neutron Activation Analysis (INAA), it is necessary to measure neutron spectrum parameters such as thermal neutron flux, the deviation from the ideal 1/E epithermal neutron flux distribution (α), and the thermal-to-epithermal neutron flux ratio (f) for the irradiation holes. In this study, the MCNP6.1 code and FORTRAN 90 language are applied to determine the parameters for the two irradiation holes (NA-SW and NA-NW) in H-LPRR, and in particular its α and f parameters are compared to values of other research reactors. The results confirmed that the neutron irradiation holes in H-LPRR are designed to be sufficiently applied to neutron activation analysis, and its performance is comparable to that of foreign research reactors including the TRIGA MARK II.

• The Journal of the Acoustical Society of Korea
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• v.29 no.2
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• pp.141-147
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• 2010

In this paper, we propose a new speech separation algorithm to extract and enhance the target speech signals from mixed speech signals by utilizing both magnitude and phase information. Since the previous statistical modeling algorithms assume that the log power spectrum values of the mixed speech signals are independent in the temporal and frequency domain, discontinuities occur in the resultant separated speech signals. To reduce the discontinuities, we apply a smoothing filter in the time-frequency domain. To further improve speech separation performance, we propose a statistical model based on both magnitude and phase information of speech signals. Experimental results show that the proposed algorithm improve signal-to-interference ratio (SIR) by 1.5 dB compared with the previous magnitude-only algorithms.

• Journal of Sensor Science and Technology
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• v.33 no.3
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• pp.139-146
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• 2024

Surface-enhanced Raman scattering (SERS) enables the detection of various types of π-conjugated biological and chemical molecules owing to its exceptional sensitivity in obtaining unique spectra, offering nondestructive classification capabilities for target analytes. Herein, we demonstrate an innovative strategy that provides significant machine learning (ML)-enabled predictive SERS platforms through surface-engineered graphene via complementary hybridization with Au nanoparticles (NPs). The hybridized Au NPs/graphene SERS platforms showed exceptional sensitivity (10^-7 M) due to the collaborative strong correlation between the localized electromagnetic effect and the enhanced chemical bonding reactivity. The chemical and physical properties of the demonstrated SERS platform were systematically investigated using microscopy and spectroscopic analysis. Furthermore, an innovative strategy employing ML is proposed to predict various analytes based on a featured Raman spectral database. Using a customized data-preprocessing algorithm, the feature data for ML were extracted from the Raman peak characteristic information, such as intensity, position, and width, from the SERS spectrum data. Additionally, sophisticated evaluations of various types of ML classification models were conducted using k-fold cross-validation (k = 5), showing 99% prediction accuracy.

• BMB Reports
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• v.57 no.7
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• pp.318-323
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• 2024

Regulation of cell fate and lung cell differentiation is associated with Aminoacyl-tRNA synthetases (ARS)-interacting multifunctional protein 2 (AIMP2), which acts as a non-enzymatic component required for the multi-tRNA synthetase complex. In response to DNA damage, a component of AIMP2 separates from the multi-tRNA synthetase complex, binds to p53, and prevents its degradation by MDM2, inducing apoptosis. Additionally, AIMP2 reduces proliferation in TGF-β and Wnt pathways, while enhancing apoptotic signaling induced by tumor necrosis factor-α. Given the crucial role of these pathways in tumorigenesis, AIMP2 is expected to function as a broad-spectrum tumor suppressor. The full-length AIMP2 transcript consists of four exons, with a small section of the pre-mRNA undergoing alternative splicing to produce a variant (AIMP2-DX2) lacking the second exon. AIMP2-DX2 binds to FBP, TRAF2, and p53 similarly to AIMP2, but competes with AIMP2 for binding to these target proteins, thereby impairing its tumor-suppressive activity. AIMP2-DX2 is specifically expressed in a diverse range of cancer cells, including breast cancer, liver cancer, bone cancer, and stomach cancer. There is growing interest in AIMP2-DX2 as a promising biomarker for prognosis and diagnosis, with AIMP2-DX2 inhibition attracting significant interest as a potentially effective therapeutic approach for the treatment of lung, ovarian, prostate, and nasopharyngeal cancers.

• Wind and Structures
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• v.39 no.2
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• pp.125-140
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• 2024

The simulation of non-stationary wind velocity is particularly crucial for the wind resistant design of slender structures. Recently, some data-driven simulation methods have received much attention due to their straightforwardness. However, as the number of simulation points increases, it will face efficiency issues. Under such a background, in this paper, a time-varying coherence matrix decomposition method based on Diagonal Proper Orthogonal Decomposition (DPOD) interpolation is proposed for the data-driven simulation of non-stationary wind velocity based on S-transform (ST). Its core idea is to use coherence matrix decomposition instead of the decomposition of the measured time-frequency power spectrum matrix based on ST. The decomposition result of the time-varying coherence matrix is relatively smooth, so DPOD interpolation can be introduced to accelerate its decomposition, and the DPOD interpolation technology is extended to the simulation based on measured wind velocity. The numerical experiment has shown that the reconstruction results of coherence matrix interpolation are consistent with the target values, and the interpolation calculation efficiency is higher than that of the coherence matrix time-frequency interpolation method and the coherence matrix POD interpolation method. Compared to existing data-driven simulation methods, it addresses the efficiency issue in simulations where the number of Cholesky decompositions increases with the increase of simulation points, significantly enhancing the efficiency of simulating multivariate non-stationary wind velocities. Meanwhile, the simulation data preserved the time-frequency characteristics of the measured wind velocity well.

• Progress in Medical Physics
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• v.29 no.1
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• pp.29-41
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• 2018

The objective of this study was to evaluate the chemical exchange saturation transfer (CEST) effect of amino acids and neurotransmitters, which exist in the human brain, depending on the concentration, pH, and amplitude of the saturation radiofrequency field. Phantoms were developed with asparagine (Asn), ${\gamma}-aminobutyric$ acid (GABA), glutamate (Glu), glycine (Gly), and myoinositol (MI). Each chemical had three different concentrations of 10, 30, and 50 mM and three different pH values of 5.6, 6.2, and 7.4. Full Z-spectrum CEST images for each phantom were acquired with a continuous-wave radiofrequency (RF) saturation pulse with two different $B_1$ amplitudes of $2{\mu}T$ and $4{\mu}T$ using an animal 9.4T MRI system. A voxel-based CEST asymmetry was mapped to evaluate exchangeable protons based on amide (-NH), amine ($-NH_2$), and hydroxyl (-OH) groups for the five target molecules. For all target molecules, the CEST effect was increased with increasing concentration and B1 amplitude; however, the CEST effect with varying pH displayed a different trend depending on the characteristics of the molecule. On CEST asymmetric maps, Glu and MI were well visualized around 3.0 and 0.9 ppm, respectively, and were well separated macroscopically at a pH of 7.4. The exchange rates of Asn, Glu, BABA, and Gly usually decreased with increasing pH. The CEST effect was dependent on the concentration, acidity of the target molecules, and B1 amplitude of the saturation RF pulse. The CEST effect for Asn can be observed in a 9.4T MRI system. The results of this study are based on applying the CEST technique in patients with neurodegenerative diseases when proteins in the brain are increased with disease progression.

• Journal of radiological science and technology
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• v.38 no.4
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• pp.451-461
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• 2015

In megavoltage (MV) radiotherapy, delivering the dose to the target volume is important while protecting the surrounding normal tissue. The purpose of this study was to evaluate the modulation transfer function (MTF), the noise power spectrum (NPS), and the detective quantum efficiency (DQE) using an edge block in megavoltage X-ray imaging (MVI). We used an edge block, which consists of tungsten with dimensions of 19 (thickness) ${\times}$ 10 (length) ${\times}$ 1 (width) $cm^3$ and measured the pre-sampling MTF at 6 MV energy. Various radiation therapy (RT) devices such as TrueBeam$^{TM}$ (Varian), BEAMVIEW$^{PLUS}$ (Siemens), iViewGT (Elekta) and Clinac$^{(R)}$iX (Varian) were used. As for MTF results, TrueBeam$^{TM}$(Varian) flattening filter free(FFF) showed the highest values of $0.46mm^{-1}$ and $1.40mm^{-1}$ for MTF 0.5 and 0.1. In NPS, iViewGT (Elekta) showed the lowest noise distribution. In DQE, iViewGT (Elekta) showed the best efficiency at a peak DQE and $1mm^{-1}DQE$ of 0.0026 and 0.00014, respectively. This study could be used not only for traditional QA imaging but also for quantitative MTF, NPS, and DQE measurement for development of an electronic portal imaging device (EPID).

• The Journal of Engineering Geology
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• v.14 no.1
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• pp.29-46
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• 2004

It is important to identify geometries of fracture that act as a conduit of fluid flow for characterization of ground water flow in fractured rock. Fracture geometries control hydraulic conductivity and stream lines in a rock mass. However, we have difficulties to acquire whole geometric data of fractures in a field scale because of discontinuous distribution of outcrops and impossibility of continuous collecting of subsurface data. Therefore, it is needed to develop a method to describe whole feature of a target fracture geometry. This study suggests a new approach to develop a method to characterize on the whole feature of a target fracture geometry based on the Fourier transform. After sampling of specimens along a target fracture from borehole cores, effective frequencies among roughness components were selected by the Fourier transform on each specimen. Then, the selected effective frequencies were averaged on each frequency. Because the averaged spectrum includes all the frequency profiles of each specimen, it shows the representative components of the fracture roughness of the target fracture. The inverse Fourier transform is conducted to reconstruct an averaged whole roughness feature after low pass filtering. The reconstructed roughness feature also shows the representative roughness of the target subsurface fracture including the geometrical characteristics of each specimen. It also means that overall roughness feature by scaling up of a fracture. In order to identify the characteristics of permeability coefficients along the target fracture, fracture models were constructed based on the reconstructed roughness feature. The computation of permeability coefficient was performed by the homogenization analysis that can calculate accurate permeability coefficients with full consideration of fracture geometry. The results show a range between $10^{-4}{\;}and{\;}10^{-3}{\;}cm/sec$, indicating reasonable values of permeability coefficient along a large fracture. This approach will be effectively applied to the analysis of permeability characteristics along a large fracture as well as identification of the whole feature of a fracture in a field scale.