• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.5
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• pp.65-70
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• 2015

Lightning is one of hazards affecting the rapid-transit railway system. There are two effects, which are direct lightning surge to electric car line and induced lightning surge. Protection methods for the direct lightning surge are studied with various occasions, however, study of induced lightning surge is insufficient in spite of a large or small effects. In this paper, it is analysed the way that serge voltage is induced to electric car line by lightning strikes. By modeling the propagation process and the coupling phenomenon of electromagnetic wave produced by lightning strikes, it is achieved to make integrative circuit model combined with existing electric car model. The study is conducted into three different waveform of electromagnetic wave produced by lightning; rectangular wave, double exponential distribution wave, triangle wave. It is also simulated that the inducing serge is coupled to electric car line in an arbitrary location. The simulation results in that, when rapidly changing rectangular wave is supplied, maximum power is induced to electric car line.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.908-928
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• 2022

Multiple target tracking mainly focuses on tracking unknown number of targets in the complex environment of clutter and missed detection. The generalized labeled multi-Bernoulli (GLMB) filter has been shown to be an effective approach and attracted extensive attention. However, in the scenarios where the clutter rate is high or measurement-outliers often occur, the performance of the GLMB filter will significantly decline due to the Gaussian-based likelihood function is sensitive to clutter. To solve this problem, this paper presents a robust GLMB filter and smoother to improve the tracking performance in the scenarios with high clutter rate, low detection probability, and measurement-outliers. Firstly, a Student-T distribution variational Bayesian (TDVB) filtering technology is employed to update targets' states. Then, The likelihood weight in the tracking process is deduced again. Finally, a trajectory smoothing method is proposed to improve the integrative tracking performance. The proposed method are compared with recent multiple target tracking filters, and the simulation results show that the proposed method can effectively improve tracking accuracy in the scenarios with high clutter rate, low detection rate and measurement-outliers. Code is published on GitHub.

• Smart Structures and Systems
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• v.30 no.4
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• pp.421-432
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• 2022

Regarding the high significance of correct pan evaporation modeling, this study introduces two novel neuro-metaheuristic approaches to improve the accuracy of prediction for this parameter. Vortex search algorithms (VSA), sunflower optimization (SFO), and stochastic fractal search (SFS) are integrated with a multilayer perceptron neural network to create the VSA-MLPNN, SFO-MLPNN, and SFS-MLPNN hybrids. The climate data of Arcata-Eureka station (operated by the US environmental protection agency) belonging to the years 1986-1989 and the year 1990 are used for training and testing the models, respectively. Trying different configurations revealed that the best performance of the VSA, SFO, and SFS is obtained for the population size of 400, 300, and 100, respectively. The results were compared with a conventionally trained MLPNN to examine the effect of the metaheuristic algorithms. Overall, all four models presented a very reliable simulation. However, the SFS-MLPNN (mean absolute error, MAE = 0.0997 and Pearson correlation coefficient, R_P = 0.9957) was the most accurate model, followed by the VSA-MLPNN (MAE = 0.1058 and R_P = 0.9945), conventional MLPNN (MAE = 0.1062 and R_P = 0.9944), and SFO-MLPNN (MAE = 0.1305 and R_P = 0.9914). The findings indicated that employing the VSA and SFS results in improving the accuracy of the neural network in the prediction of pan evaporation. Hence, the suggested models are recommended for future practical applications.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.1009-1014
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• 2023

Muon tomography is a useful method for monitoring special nuclear materials (SNMs) such as spent nuclear fuel inside dry cask storage. Multiple Coulomb scattering of muons can be used to provide information about the 3-dimensional structure and atomic number(Z) of the inner materials. Tomography using muons is less affected by the shielding material and less harmful to health than other measurement methods. We developed a muon detector for muon tomography, which consists of a plastic scintillator, 64 long wavelength-shifting (WLS) fibers attached to the top of the plastic scintillator, and silicon photomultipliers (SiPMs) connected to both ends of each WLS fiber. The muon detector can acquire X and Y positions simultaneously using a position determination algorithm. The design parameters of the muon detector were optimized using DETECT2000 and Geant4 simulations, and a muon detector prototype was built based on the results. Spatial resolution measurement was performed using simulations and experiments to evaluate the feasibility of the muon detector. The experimental results were in good agreement with the simulation results. The muon detector has been confirmed for use in a muon tomography system.

• Journal of Integrative Natural Science
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• v.17 no.1
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• pp.13-20
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• 2024

Female breast cancer is the fifth highest cause of mortality. Breast cancer is the most prevalent type of cancer in women globally, while it can also affect men. STAT5A plays a role in its development and progression. Given that activation of STAT5a is frequently linked to the growth and progression of tumors, STAT5a has been identified as a possible target for the therapy of several cancers. STAT5A, in particular, has proven to be overexpressed in various breast cancer cell lines and tumors, and it has been associated to the promotion of tumour cell proliferation and survival. STAT5A inhibition has been shown in vitro and in vivo to reduce the development of breast cancer cells. As a result, we have screened compounds from the FDA database that might serve as potential inhibitors of STAT5a through virtual screening, docking, DFT and MD simulation approaches. The drug Nilotinib has shown promising results inhibiting STAT5a. Further, in-vitro analysis will be carried forward to understand the anti-cancer activity.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.326-338
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• 2003

The objective of a neural network design and model selection is to construct an optimal network with a good generalization performance. However, training data include noises, and the number of training data is not sufficient, which results in the difference between the true probability distribution and the empirical one. The difference makes the teaming parameters to over-fit only to training data and to deviate from the true distribution of data, which is called the overfitting phenomenon. The overfilled neural network shows good approximations for the training data, but gives bad predictions to untrained new data. As the complexity of the neural network increases, this overfitting phenomenon also becomes more severe. In this paper, by taking statistical viewpoint, we proposed an integrative process for neural network design and model selection method in order to improve generalization performance. At first, by using the natural gradient learning with adaptive regularization, we try to obtain optimal parameters that are not overfilled to training data with fast convergence. By adopting the natural pruning to the obtained optimal parameters, we generate several candidates of network model with different sizes. Finally, we select an optimal model among candidate models based on the Bayesian Information Criteria. Through the computer simulation on benchmark problems, we confirm the generalization and structure optimization performance of the proposed integrative process of teaming and model selection.

• Current Optics and Photonics
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• v.1 no.1
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• pp.51-59
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• 2017

In addition to its typical use for skin rejuvenation, fractional laser irradiation of early cancerous lesions may reduce the risk of tumor development as a byproduct of wound healing in the stroma after the controlled injury. While fractional ablative lasers are commonly used for cosmetic/aesthetic purposes (e.g., photorejuvenation, hair removal, and scar reduction), we propose a novel use of such laser treatments as a stromal treatment to delay tumorigenesis and suppress carcinogenesis. In this study, we found that non-ablative fractional laser (NAFL) irradiation may have a possible suppressive effect on early tumor growth in syngeneic mouse tumor models. We included two syngeneic mouse tumor models in irradiation groups and control groups. In the irradiation group, a thulium fiber based NAFL at 1927 nm was used to irradiate the skin area including the tumor injection region with 70 mJ/spot, while no laser irradiation was applied to the control group. Numerical simulation with the same experimental condition showed that thermal damage was confined only to the irradiation spots, sparing the adjacent tissue area. The irradiation groups of both tumor models showed smaller tumor volumes than the control group at an early tumor growth stage. We also detected elevated inflammatory cytokine levels a day after the NAFL irradiation. NAFL treatment of the stromal tissue could potentially be an alternative anticancer therapeutic modality for early tumorigenesis in a minimally invasive manner.

• Journal of the Microelectronics and Packaging Society
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• v.18 no.3
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• pp.59-65
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• 2011

According to the trends of electronic package to be smaller, thinner and more integrative, Flip Chip Ball Grid Array (FCBGA) become more used for mobile phone. However, the flip chip necessarily generate the heat by the electrical resistance and generated heat is increased due to reduced distribution area of the heat in accordance with the miniaturization trend of the package. Thermal issues can result in problems of devices that are sensitive to temperature and stress. Then the heat can generate problems to the system. In this paper, in order to improve the thermal issues of FCBGA, thermal characteristics of FCBGA was analyzed qualitatively by using the general heat transfer module of Comsol 3.5a and In order to solve thermal issues, flip chip with new micro structure is proposed by the simulation. and also by comparing existing model and analyzing variables such as pitch, height of the pattern and shape of the heat spreader, the improvement of heat dissipation characteristics about 18% was confirmed.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.1
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• pp.1-7
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• 2007

An MTJ element not only computes Boolean function but also stores the output result in itself. We can make the most use of magneto-logic's merits by employing the magneto-logic in substitution for the sequential logic as well as the combinational logic. This unique feature opens a new horizon for potential application of MTJ as a universal logic element. Magneto-logic circuits using MTJ elements are more integrative and non-volatile. This paper presents novel 3-bit magneto-logic up/down counters and presents simulation results based on the HSPICE macro-model of MTJ that we have developed.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.2
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• pp.175-181
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• 2016

In the conventional E-bike, a 42 V/10 A Li-ion battery drives a 24 V/10 A BLDC motor via a 6-switch PWM DC/AC inverter. The major problems of the conventional battery-fed motor drive systems are listed as follows. To charge the battery, an external battery charger (adapter) is required, which degrades the portability of E-bike users. In addition, given the high-frequency operation of the motor drive inverter, the switching losses are significant, which degrades the whole power efficiency. High-voltage batteries (42 V) require a complex battery management system (BMS), which degrades the reliability of the battery pack. In this paper, an embedded boost-converter battery charger for E-bikes is proposed. The variable output boost converter, which converts 16.8 V battery voltage to the required variable voltage of the inverter input, can use a low-voltage battery and thus improve the reliability of batteries. By varying the inverter input voltage via boost converter, a DC link voltage control method can be applied to reduce the switching frequency of the inverter, which improves the whole power efficiency. Given that the function of a flyback charger is integrated in the proposed boost converter, the portability of the E-bike user can be maximized by excluding an external adapter. The validity of the proposed circuit will be confirmed by operation mode analysis and simulation. Moreover, experimental results of integrative charger using Li-ion battery and 200 W motor test will be showed with a prototype sample as well.