Jo Oct 23, 2026
In several fields such as space engineering, it is very important to evaluate the performance degradation of electronic components by high-energy protons.
Charged particles such as protons cause excitation or ionization in semiconductor crystals. However, a very small fraction of the energy loss is then used to displace atoms from their equilibrium positions to create primary displacement atoms (non-ionizing processes). The generated primary displacement atoms cause cascade processes by displacing many atoms, which proceed until the transferred energy becomes smaller than the threshold required to displace the atoms. In the space environment, the defects created by incident particles create new energy levels within the band gap, and the levels change the electrical and optical properties of the electronic device and material. In other words, the protons in space environment cause single-event effects (SEE), total ionization dose (TID) effects, and displacement damage dose (DDD) effects in the electronic device.
In terms of the proton-induced DDD effect, the most sensitive electronic component is bipolar devices. Generally, proton accelerators, 1 MeV neutron source, and 1 MeV electron source are used to estimate the DDD effect in bipolar devices.
Considering the high cost for testing these methods, Kang Myong Chol, a section head at the Faculty of Electronics, proposed a method of evaluating the proton-induced DDD effect on the bipolar devices by using the existing Pu-Be isotope neutron source. Then, he verified the accuracy of the proton-induced DDD effect estimation using the Pu-Be isotope neutron source by using the optocouplers, TLP521-1GB and PC817C.
The proposed method can be used to evaluate the durability of electronic devices operating in proton environments.
You can find more information in his paper “Proton Induced Damage Estimation in Bipolar Device” in “Proceedings of KUTIC-2025”.
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Jo Oct 22, 2026
Direct methanol fuel cells (DMFCs) exhibit some advantages such as easy storage and transportation of fuel, and high specific energy density, compared to lithium batteries. However, there are still many problems in the widespread use of passive DMFC as lithium batteries.
One of the problems is the rapid removal of carbon dioxide at the anode to enhance the performance of passive DMFC. Carbon dioxide removal depends on the structure of the anode flow field (AFF), MEA and even operating conditions. Most of the efforts to effectively remove carbon dioxide have focused on reducing the bubble resistance of CO2 by improving the structure and shape of AFF.
However, efforts to reduce the negative impact of CO2 gas in MEA have not reached complete separation of two-phase flow in the anode gas diffusion layer (AGDL).
Jon Song Hyok, a researcher at the Faculty of Chemical Engineering, has proposed a new anode gas diffusion layer (AGDL) structure that can overcome the effects of two-phase flow in the MEA, the core of passive DMFC.
Using the anode carbon paper hydrophobically treated with 50wt.% PTFE loading, carbon dioxide is released to the lateral venting channels and methanol is allowed to be fed through a hole in the middle of the carbon paper.
Compared to the conventional DMFC, this improved AGDL provided a stable operating environment by separating the two-phase flow inside the cell and showed good performance with the maximum power density 17.3mW/cm2 at 12.0M methanol concentration.
If more information is needed, please refer to his paper “Efficient CO2 Removal by Improving Diffusion Layer Structure in Methanol Fuel Cells” in “Proceedings of KUTIC-2025”.
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Jo Oct 21, 2026
When a vehicle reenters the earth’s atmosphere at a hypersonic speed, the surrounding air molecules are dissociated and ionized by the tremendous heat due to atmospheric friction, and a plasma sheath surrounding the hypersonic vehicle’s surface will be formed. The plasma sheath greatly attenuates the electromagnetic (EM) waves radiated from an onboard antenna through reflection and absorption effects, and intermittent communication outage and blackout are frequently caused by the plasma sheath. Therefore, research on the interaction mechanism between EM waves and plasma sheath is of great significance.
Many studies have been conducted on the propagation characteristics of EM waves at the plasma sheath. However, the propagations of obliquely incident EM waves in the reentry plasma sheath have not been actively studied, and only a few studies dealt with it.
Han Yong Su, a researcher at the Faculty of Physics, has investigated the propagation properties of obliquely incident S-polarization electromagnetic waves into reentry plasma with bi-Gaussian electron density profile.
Based on the continuous boundary condition of electromagnetic (EM) waves in multilayer plasma, he deduced a scattering matrix equation of the obliquely incident S-polarization EM wave, and investigated the properties of reflection, transmission and absorption in terms of incident angle, plasma electron density distribution, and collision frequency, respectively.
The numerical results show that when the incident EM wave obliquely passes through the plasma sheath, the amplitudes of reflectance, transmittance and absorptivity are obviously modulated by the incident angle, electron density profile, and collision frequency. In addition, he confirmed that the transmittance peak and absorptivity peak are shifted from a lower frequency to a higher frequency with the increase in the incident angle, electron density profile and collision frequency.
You can find more information in his paper “Numerical Investigation for Propagation Characteristics of Obliquely Incident EM Waves in Plasma Sheath” in “Proceedings of KUTIC-2025”.
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Jo Oct 20, 2026
Dynamic time-warping is a method of matching by computing similarity using the elastic distance between two time series. This method was developed for speech recognition and it has been applied to many areas.
This matching method makes one time series to be compressed and stretched nonlinearly in the time axis direction based on the dynamic programming to minimize the elastic distance between two time series of different lengths.
In the literature, matching is implemented by changing the scale of time axis in the time series.
Jong Sung Il, a lecturer at the Faculty of Applied Mathematics, has proposed a time-phase scale varying DTW method of implementing matching by varying the scale of phase as well as that of time axis. Then, he applied it to a sine function with varying amplitude to verify its effectiveness.
For further details, please refer to his paper “Pattern Detection Method using Phase Varying Dynamic Time Warping in Time Series” in “Proceedings of KUTIC-2025”.
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Jo Oct 19, 2026
In recent years, with the rapid popularization of intelligent terminals and sensors, massive data have been accumulated rapidly, and the processing technology of big data has attracted more and more attention. Among them, large information data with functional characteristics such as physiological data, growth curve data, temperature data, etc. are also attracting significant attention. In fact, these data are discrete samples of continuous functions, and these data are usually known as functional data.
The main problem in functional data analysis is dimensionality reduction, and one of the common ways to reduce dimension is to take only a few principal components by performing functional principal component analysis (PCA) on given functional data. The conventional functional principal component analysis method uses the L2-norm, which has the advantage of being computationally convenient, but it is not efficient for data with outliers because the L2-norm is highly affected by outliers. It can be expected that the PCA method using the L1-norm instead of the L2-norm will have better robustness. Without considering the computational complexity when using the L1-norm, high computational cost of functional data analysis cannot be avoided.
Paek Hyon I, a researcher at the Faculty of Applied Mathematics, proposed a method for improving robustness by using L1-norm instead of L2-norm in the functional principal component analysis for functional data with vertical outliers, and constructed an efficient computational algorithm to reduce computational complexity.
This algorithm can achieve more efficient functional principal components with high robustness from data contaminated by vertical outliers while reducing the computational complexity of functional principal component analysis.
It was demonstrated through modeling studies that this method is more robust to outliers than L2-norm functional principal component analysis.
You can find details in his paper “L1-norm Principal Component Analysis Method for Functional Data with Vertical Outliers” in “Proceedings of KUTIC-2025”.
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Jo Oct 18, 2026
Kim Ung, a section head at the Faculty of Applied Mathematics, has studied a deterministic infinite horizon, a mixed continuous and impulse control problem with unbounded cost functional.
Major difficulties arise from the unboundedness of value functions.
He proved the comparison result of viscosity solution by converting unbounded value functions into bounded ones by suitable transformation and proved that the value function is the unique viscosity solution of the related first order Hamilton-Jacobi quasi-variational inequality (QVI). He constructed a time-discretization scheme for the QVI and proved that an approximate value function exists and it is the unique solution of the approximate QVI.
He also proved that the solution of the time discrete scheme converges to the viscosity solution of the QVI, when the discretization step goes to zero, and that the optimal control of the time discrete system determined by the corresponding dynamic programming is a minimizing sequence of the optimal feedback control of the impulse control problem.
You can find more information in his paper “Approximation Schemes for Impulse Control Systems with Unbounded Cost Functional” in “Proceedings of KUTIC-2025”.
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