• Korean Journal of Medicinal Crop Science
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• v.27 no.2
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• pp.75-85
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• 2019

Background: Medicinal plants are widely used in Asia. They have proven to be an invaluable asset in modern drug discovery and their demand has been steadily increasing across various industries. Methods and Results: Using 4,867 valid patents related to 12 oriental medicinal plants of 10 country groups, the growth and development potential of patents was evaluated. The cites per patent (CPP) and patent family size (PFS) indices were used to evaluate the market capability and technological level of the collected patents. Meanwhile, the patent impact index (PII) and technology strength (TS) were used to compare the technological competitiveness of patents among various technology types and markets. Both CPP and PFS indices showed that magnolia-vine and balloon flower have numerous core or original patents. Furthermore, an increase in both PII and TS indices was observed. A newly designed intellectual property multi-layer (IPM) model predicted that the medicine, genome and cosmetic categories have a high possibility of patent application growth. Conclusions: The IPM model can be used to provide the scope of particular technology fields for patent development. In addition, this study can assist patents to advance in the international market and guide the development of a national industrial strategy.

• Journal of the Korea Safety Management & Science
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• v.20 no.4
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• pp.7-13
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• 2018

This study investigates the enhancement of the oxygen diffusion rate in the cathode channel of a proton exchange membrane fuel cell (PEMFC) by pure oscillating flow, which is the same as the mechanism of human breathe. Three-dimensional numerical simulation, which has the full model of the fuel cell including electrochemical reaction, ion and electronic conduction, mass transfer and thermal variation and so on, is performed to show the phenomena in the channel at the case of a steady state. This model could analysis the oscillating flow as a moving mesh calculation coupled with electrochemical reaction on the catalyst layer, however, it needs a lot of calculation time for each case. The two dimensional numerical simulation has carried on for the study of oscillating flow effect in the cathode channel of PEMFC in order to reduce the calculation time. This study shows the diffusion rate of the oxygen increased and the emission rate of the water vapor increased in the channel by oscillating flow without any forced flow.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2204-2224
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• 2021

This paper studies secure wireless transmission from a multi-antenna transmitter to a single-antenna intended receiver overheard by multiple eavesdroppers with considering the imperfect channel state information (CSI) of wiretap channel. To enhance security of communication link, the artificial noise (AN) is generated at transmitter. We first design the robust joint optimal beamforming of secret signal and AN to minimize transmit power with constraints of security quality of service (QoS), i.e., minimum allowable signal-to-interference-and-noise ratio (SINR) at receiver and maximum tolerable SINR at eavesdroppers. The formulated design problem is shown to be nonconvex and we transfer it into linear matrix inequalities (LMIs). The semidefinite relaxation (SDR) technique is used and the approximated method is proved to solve the original problem exactly. To verify the robustness and tightness of proposed beamforming, we also provide a method to calculate the worst-case SINR at eavesdroppers for a designed transmit scheme using semidefinite programming (SDP). Additionally, the secrecy rate maximization is explored for fixed total transmit power. To tackle the nonconvexity of original formulation, we develop an iterative approach employing sequential parametric convex approximation (SPCA). The simulation results illustrate that the proposed robust transmit schemes can effectively improve the transmit performance.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1540-1551
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• 2020

Aiming at the problem that the existing human behavior recognition algorithm cannot fully utilize the multi-level spatio-temporal information of the network, a human behavior recognition algorithm based on a dense three-dimensional residual network is proposed. First, the proposed algorithm uses a dense block of three-dimensional residuals as the basic module of the network. The module extracts the hierarchical features of human behavior through densely connected convolutional layers; Secondly, the local feature aggregation adaptive method is used to learn the local dense features of human behavior; Then, the residual connection module is applied to promote the flow of feature information and reduced the difficulty of training; Finally, the multi-layer local feature extraction of the network is realized by cascading multiple three-dimensional residual dense blocks, and use the global feature aggregation adaptive method to learn the features of all network layers to realize human behavior recognition. A large number of experimental results on benchmark datasets KTH show that the recognition rate (top-l accuracy) of the proposed algorithm reaches 93.52%. Compared with the three-dimensional convolutional neural network (C3D) algorithm, it has improved by 3.93 percentage points. The proposed algorithm framework has good robustness and transfer learning ability, and can effectively handle a variety of video behavior recognition tasks.

• Corrosion Science and Technology
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• v.21 no.3
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• pp.171-183
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• 2022

The performance and inhibitory action of the aqueous extract of Cyperus Conglomeratus's leaves against corrosion of XC70 steel in a 1M HCl acid medium are studied by the determination of the weight loss, the potentiodynamic polarization curves analysis, and electrochemical impedance measurements (electrochemical techniques). The corrosion inhibitory efficiency of XC70 steel increases with the increasing concentration of the green inhibitor, however, the corrosion rate of the steel decreases. Weight loss measurements show that the maximum percentage corrosion inhibition efficiency is approximately 61.86%, while the analysis of the mixed character polarization curves shows that the inhibitor could achieve an inhibition efficiency of 86.96%. The electrochemical impedance study confirmed that the value of the charge transfer resistance (R_ct) increases and the value of the double layer capacity (C_dl) decreases with increasing concentration of the aqueous extract of Cyperus Conglomeratus's leaves, thus increasing the inhibition efficiency. The study showed that this aqueous extract acts by adsorption on the metal surface; this adsorption follows the Langmuir isotherm. This research work showed that Cyperus Conglomeratus leaves extract acts as an effective and eco-friendly inhibitor on mild steel in an acid medium.

• Current Optics and Photonics
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• v.6 no.3
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• pp.270-281
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• 2022

Based on the transfer-matrix method (TMM), we report the characteristics of the interface states in one-dimensional (1D) composite structures consisting of two photonic crystals (PCs) composed of binary dielectrics A and B, with unit-cell configurations ABA (PC I) and BAB (PC II). The dependence of the interface states on the number of unit cells N and the boundary factor x are displayed. It is verified that the interface states are independent of N when the PC has inversion symmetry (x = 0.5). Besides, the composite structures support the formation of interface states independent of the PC symmetry, except that the positions of the interface states will be varied within the photonic band gaps. Moreover, the robustness of the interface states against nonuniformities is investigated by adding Gaussian noise to the layer thickness. In the case of inversion symmetry (x = 0.5) the most robust interface states are achieved, while for the other cases (x ≠ 0.5) interface states decay linearly with position inside the band gap. This work could shed light on the development of robust photonic devices.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.1962-1971
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• 2022

The liquid lead-lithium (Pb-17Li) blanket has many applications in fusion reactors due to its good tritium breeding performance, high heat transfer efficiency and safety. The compatibility of liquid Pb-17Li alloy with the structural material of blanket under magnetic field is one of the concerns. In this study, corrosion experiments China low activation martensitic (CLAM) steel and 316L steel were carried out in a forced convection Pb-17Li loop under 1.0 T magnetic field at 480 ℃ for 1000 h. The corrosion results on 316L steel showed the characteristic with a superficial porous layer resulted from selective leaching of high-soluble alloy elements and subsequent phase transformation from austenitic matrix to ferritic phase. Then the porous layers were eroded by high-velocity jet fluid. The main corrosion mechanism of CLAM steel was selective dissolution-base corrosion attack on the microstructure boundary regions and exclusively on high residual stress areas. CLAM steel performed a better corrosion resistance than that of 316L steel. The high Ni dissolution rate and the erosion of corroded layers are the main causes for the severe corrosion of 316L steel.

• Journal of Sensor Science and Technology
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• v.31 no.4
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• pp.238-243
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• 2022

In this study, a pyrene-core single molecule with amino (-NH₂) functional group material was hybridized using ZnO quantum dots (QDs). The suppressed performance of the 1-aminopyrene (1-PyNH₂) single molecule as an emissive layer (EML) in light-emitting diodes (LEDs) was exploited by adopting the ZnO@1-PyNH₂ core-shell structure. Unlike pristine 1-PyNH₂ molecules, the ZnO@1-PyNH₂ hybrid QDs formed energy proximity levels that enabled charge transfer. This result can be interpreted as an improvement in surface roughness. The uniform and homogeneous EML alleviates dark-spot degradation. Moreover, LEDs with the ITO/PEDOT:PSS/TFB/EML/TPBi/LiF/Al configuration were fabricated to evaluate the performance of two emissive materials, where pristine-1-PyNH₂ molecules and ZnO@1-PyNH₂ QDs were used as the EML materials to verify the improvement in electrical characteristics. The ZnO@1-PyNH₂ LEDs exhibited blue luminescence at 443 nm (FWHM = 49 nm), with a turn-on voltage of 4 V, maximum luminance of 1500 cd/m², maximum luminous efficiency of 0.66 cd/A, and power efficiency of 0.41 lm/W.

• Membrane and Water Treatment
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• v.13 no.6
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• pp.313-320
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• 2022

Theoretical calculation results are presented for the enhancement of the water mass flow rate through the hydrophobic micro/nano pores in the membrane respectively on the micrometer and nanometer scales. The water-pore wall interfacial slippage is considered. When the pore diameter is critically low (less than 1.82nm), the water flow in the nanopore is non-continuum and described by the nanoscale flow equation; Otherwise, the water flow is essentially multiscale consisting of both the adsorbed boundary layer flow and the intermediate continuum water flow, and it is described by the multiscale flow equation. For no wall slippage, the calculated water flow rate through the pore is very close to the classical hydrodynamic theory calculation if the pore diameter (d) is larger than 1.0nm, however it is considerably smaller than the conventional calculation if d is less than 1.0nm because of the non-continuum effect of the water film. When the driving power loss on the pore is larger than the critical value, the wall slippage occurs, and it results in the different scales of the enhancement of the water flow rate through the pore which are strongly dependent on both the pore diameter and the driving power loss on the pore. Both the pressure drop and the critical power loss on the pore for starting the wall slippage are also strongly dependent on the pore diameter.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.4
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• pp.217-228
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• 2022

Currently, there are increasing demands for applying deep neural networks (DNNs) in the embedded domain such as classification and object detection. The DNN processing in embedded domain often requires custom hardware such as NPU for acceleration due to the constraints in power, performance, and area. Processing DNN models requires a large amount of data, and its seamless transfer to NPU is crucial for performance. In this paper, we developed a cycle-accurate NPU simulator to evaluate diverse NPU microarchitectures. In addition, we propose a novel technique for reducing the number of memory accesses when processing convolutional layers in convolutional neural networks (CNNs) on the NPU. The main idea is to reuse data with memory interleaving, which recycles the overlapping data between previous and current input windows. Data memory interleaving makes it possible to quickly read consecutive data in unaligned locations. We implemented the proposed technique to the cycle-accurate NPU simulator and measured the performance with LeNet-5, VGGNet-16, and ResNet-50. The experiment shows up to 2.08x speedup in processing one convolutional layer, compared to the baseline.