• ETRI Journal
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• v.33 no.6
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• pp.857-863
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• 2011

Due to uncertainties in target motion and randomness of deployed sensor nodes, the problem of imbalance of energy consumption arises from sensor scheduling. This paper presents an energy-efficient adaptive sensor scheduling for a target monitoring algorithm in a local monitoring region of wireless sensor networks. Owing to excessive scheduling of an individual node, one node with a high value generated by a decision function is preferentially selected as a tasking node to balance the local energy consumption of a dynamic clustering, and the node with the highest value is chosen as the cluster head. Others with lower ones are in reserve. In addition, an optimization problem is derived to satisfy the problem of sensor scheduling subject to the joint detection probability for tasking sensors. Particles of the target in particle filter algorithm are resampled for a higher tracking accuracy. Simulation results show this algorithm can improve the required tracking accuracy, and nodes are efficiently scheduled. Hence, there is a 41.67% savings in energy consumption.

• Journal of the Korean GEO-environmental Society
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• v.11 no.12
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• pp.37-45
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• 2010

The particle size of microfine cement(MC) is so small that it can be injected into silt layer. But the more particle size is miniaturized, the more the cohesion increases. This phenomenon results in the decrease of the perviousness of MC. In this study, the grouting effects of microfine cement with superplasticizer to maintain cohesion low and that of normal cement were investigated in rock. To estimate the grouting effects, TCR/RQD test for rock quality, lugeon test, borehole loading test for coefficients of elastic and deformative stress, borehole shear test for shear stress, detection p~q~t(pressure~flow~time) chart tests were carried out. The results using MC show a better permeability, modulus of elasticity, deformation, charge per unit, and recover efficiency of grouting material than those of ordinary portland cement except shear stress.

• Journal of Sensor Science and Technology
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• v.28 no.5
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• pp.294-298
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• 2019

Pulsed laser-based optical sensor monitoring systems for real time microplastic particle counting are proposed and developed in this study. To develop our real time monitoring system, we used a 450 nm pulsed laser and a photomultiplier with very high quantum efficiency. First, we demonstrated that the microplastic particle counting system could detect standard micro bead samples of 100, 250, and $500{\mu}m$ in river water. We then performed research concerning pulsed laser-based optical spectral sensor systems for real time microplastic monitoring. Additionally, we demonstrated that the real time microplastic remote monitoring system using LoRa communications could detect microplastic in the tap water resource protection area.

• Smart Structures and Systems
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• v.22 no.5
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• pp.561-574
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• 2018

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.

• Publications of The Korean Astronomical Society
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• v.21 no.2
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• pp.87-94
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• 2006

The COREA (COsmic ray Research and Education Array in Korea) project aims to build a ground array of particle detectors distributed over Korean Peninsular, through collaborations of high school students, educators, and university researchers, in order to study the origin of ultra high energy cosmic rays. COREA array will consist of about 2000 detector stations covering several hundreds of $km^2$ area at its final configuration and detect electrons and muons in extensive air-showers triggered by high energy particles. During the intial phase COREA array will start with a small number of detector stations in Seoul area schools. In this paper, we have studied by Monte Carlo simulations how to select detector sites for optimal detection efficiency for proton triggered air-showers. We considered several model clusters with up to 30 detector stations and calculated the effective number of air-shower events that can be detected per year for each cluster. The greatest detection efficiency is achieved when the mean distance between detector stations of a cluster is comparable to the effective radius of the air-shower of a given proton energy. We find the detection efficiency of a cluster with randomly selected detector sites is comparable to that of clusters with uniform detector spacing. We also considered a hybrid cluster with 60 detector stations that combines a small cluster with ${\Delta}{\iota}{\approx}100m$ and a large cluster with ${Delta}{\iota}{\approx}1km$. We suggest that it can be an ideal configuration for the initial phase study of the COREA project, since it can measure the cosmic rays with a wide range energy, i.e., $10^{16}eV{\leq}E{\leq}10^{19}eV$, with a reasonable detection rate.

• Journal of Korea Water Resources Association
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• v.38 no.10 s.159
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• pp.841-849
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• 2005

Two-phase flows, e.g. sediment-laden flow and bubbly flow, have two different flow profiles; flow velocity and sediment velocity. To measure velocity distributions of two-phase flows, it is necessary to use sophisticated instruments which can separate velocity profiles of two-phases. For bubbly flows, PIV (Particle Image Velocimetry) or PTV (Particle Tracking Velocimetry) has given fairly good velocity profiles of two-phases. However, for sediment-laden flows, the applications of PIV or PTV has not been so successful, because the sediment particles introduced to the flow kept the images from being analyzed. A new algorithm, which consists of several image analysis methods, is proposed to analyze sediment-laden flows. For detection algorithm, threshold method, edge detection method, and thinning method are adapted, and for finding matching pair PIV and PTV routines are combined. The proposed method can (1) detect sediment particles with irregular boundaries, (2) remove reflected images and scattered images, and (3) discriminate tracer particles from reflected images of sediment particles.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.109-114
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• 2015

This paper presents a computational model on the transfer of airborne fine particles to analyze the similarities and influences among the 25 districts in Seoul by quantifying a time series data collected from each district. The properties of each district are driven with the model of a time series of the fine particle concentrations, and the calculation of edge-based weights are carried out with the transfer entropies between all pairs of the districts. We applied a modularity-based graph clustering technique to detect the communities among the 25 districts. The result indicates the discovered clusters correspond to a high transfer-entropy group among the communities with geographical adjacency or high in-between traffic volumes. We believe that this approach can be further extended to the discovery of significant flows of other indicators causing environmental pollution.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1704-1711
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• 2014

Sandy and dusty weather condition often occurs in the high altitude areas of China, which may greatly influence the corona generated radio interference (RI) characteristics of the bundle conductors of 750 kV AC power transmission lines. Corona generated RI of the conductors of the 750 kV AC power transmission lines used in practice is measured by EMI receiver with a coupling circuit and a coupling capacitor connected between the high voltage side and the earth side in fine and sandy and dusty condition. The measuring frequency is 0.5 MHz, and the quasi-peak detection is used. RI excitation function is calculated based on the corona RI current measured by the EMI receiver. Corona generated RI characteristics were analyzed from sand concentration and sand particle size. The test result shows that the corona generated RI excitation function is influenced by the sandy and dusty condition. Corona discharge of the conductors is more serious in sandy and dusty condition with an ultraviolet (UV) detector. Corona generated RI excitation function increases with the increase of sand concentration and also increases with the increase of particle size.

• Nuclear Engineering and Technology
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• v.43 no.6
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• pp.567-572
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• 2011

A sensitivity analysis of the methods used to evaluate the transport properties of a CdZnTe detector was performed using two different radiations (${\alpha}$ particle and gamma-ray) emitted from an $^{241}Am$ source. The mobility-lifetime products of the electron-hole pair in a planar CZT detector ($5{\times}5{\times}2\;mm^3$) were determined by fitting the peak position as a function of biased voltage data to the Hecht equation. To verify the accuracy of these products derived from ${\alpha}$ particles and low-energy gamma-rays, an energy spectrum considering the transport property of the CZT detector was simulated through a combination of the deposited energy and the charge collection efficiency at a specific position. It was found that the shaping time of the amplifier module significantly affects the determination of the (${\mu}{\tau}$) products; the ${\alpha}$ particle method was stabilized with an increase in the shaping time and was less sensitive to this change compared to when the gamma-ray method was used. In the case of the simulated energy spectrum with transport properties evaluated by the ${\alpha}$ particle method, the peak position and tail were slightly different from the measured result, whereas the energy spectrum derived from the low-energy gamma-ray was in good agreement with the experimental results. From these results, it was confirmed that low-energy gamma-rays are more useful when seeking to obtain the transport properties of carriers than ${\alpha}$ particles because the methods that use gamma-rays are less influenced by the surface condition of the CZT detector. Furthermore, the analysis system employed in this study, which was configured by a combination of Monte Carlo simulation and the Hecht model, is expected to be highly applicable to the study of the characteristics of CZT detectors.

• Journal of Radiation Protection and Research
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• v.44 no.2
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• pp.53-63
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• 2019

Background: As neutron fields are always accompanied by gamma rays, it is essential to distinguish neutrons from gamma rays in the detection of neutrons. Neutrons and gamma rays can be separated by pulse shape discrimination (PSD) methods. Recently, we performed characterization of a stilbene scintillator detector and an EJ-301 liquid scintillator detector with a high-speed digitizer DT5730 and investigated optimized PSD variables for both detectors. This study is for providing a basis for developing fast neutron/gamma-ray dual-particle imager. Materials and Methods: We conducted PSD experiments using stilbene scintillator and EJ-301 liquid scintillator and evaluated neutron and gamma ray discriminability of each PSD method with a $^{137}Cs$ gamma source and a $^{252}Cf$ neutron source. We implemented digital signal processing techniques to apply two PSD methods - the charge comparison (CC) method and the constant time discrimination (CTD) method - to distinguish neutrons from gamma rays. We tried to find optimized PSD variables giving the best discriminability in a given experimental condition. Results and Discussion: For the stilbene scintillator detector, the charge comparison method and the constant time discrimination method both delivered the PSD FOM values of 1.7. For the EJ-301 liquid scintillator detector, both PSD methods delivered the PSD FOM values of 1.79. With the same PSD variables, PSD performance was excellent in $300{\pm}100keVee$, $500{\pm}100keVee$, and $700{\pm}100keVee$ energy regions. This result shows that we can achieve an effective discrimination of neutrons from gamma rays using these scintillator detector systems. Conclusion: We applied both PSD methods to a stilbene and a liquid scintillator and optimized the PSD performance represented by FOM values. We observed a good separation performance of both scintillators combined with a high-speed digitizer and digital PSD. These results will provide reference values for the dual-particle imager we are developing, which can image both fast neutrons and gamma rays simultaneously.