• Korean Chemical Engineering Research
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• v.57 no.3
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• pp.425-431
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• 2019

As rechargeable metal-air batteries will be ideal energy storage devices in the future, an active cathode electrocatalyst is required with bi-functionality on both oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) during discharge and charge, respectively. Here, a class of perovskite cathode catalyst with a micro-tubular structure has been developed by controlling bi-functionality from different Ru and Ni dopant ratios. A micro-tubular structure is achieved by the activated carbon fiber (ACF) templating method, which provides uniform size and shape. At the perovskite formula of $LaCrO_3$, the dual dopant system is successfully synthesized with a perfect incorporation into the single perovskite structure. The chemical oxidation states for each Ni and Ru also confirm the partial substitution to B-site of Cr without any changes in the major perovskite structure. From the electrochemical measurements, the micro-tubular feature reveals much more efficient catalytic activity on ORR and OER, comparing to the grain catalyst with same perovskite composition. By changing the Ru and Ni ratio, the $LaCr_{0.8}Ru_{0.1}Ni_{0.1}O_3$ micro-tubular catalyst exhibits great bi-functionality, especially on ORR, with low metal loading, which is comparable to the commercial catalyst of Pt and Ir. This advanced catalytic property on the micro-tubular structure and Ru/Ni synergy effect at the perovskite material may provide a new direction for the next-generation cathode catalyst in metal-air battery system.

• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.9-15
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• 2019

Recently, in the field of next-generation e-commerce and finance, interest in blockchain-based technologies such as Bitcoin and Ethereum is great. Although the security of blockchain technology is known to be secure, hacking incidents / accidents related to cryptocurrencies are being issued. The main causes were vulnerabilities in the external environment, such as taking over login sessions on cryptocurrency wallets, exposing private keys due to malware infection, and using simple passwords. However, private key management recommends general methods such as utilizing a dedicated application or local backup and physical archiving through document printing. In this paper, we propose a white box password-based private key protection scheme. As a result of safety and performance analysis, we strengthened the security against vulnerability of private key exposure and proved the processing efficiency of existing protocol.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.10
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• pp.231-238
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• 2019

Analyzing next-generation genome sequencing data in a conventional way using single server may take several tens of hours depending on the data size. However, in order to cope with emergency situations where the results need to be known within a few hours, it is required to improve the performance of a single genome analysis. In this paper, we propose a parallelized method for pre-processing genome sequence data which can reduce the analysis time by utilizing the big data technology and the highperformance computing cluster which is connected to the high-speed network and shares the parallel file system. For the reliability of analytical data, we have chosen a strategy to parallelize the existing analytical tools and algorithms to the new environment. Parallelized processing, data distribution, and parallel merging techniques have been developed and performance improvements have been confirmed through experiments.

• Korean Journal of Metals and Materials
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• v.56 no.12
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• pp.910-914
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• 2018

Since catalyst technology is one of the promising technologies to improve the working performance of next generation energy and electronic devices, many efforts have been made to develop various catalysts with high efficiency at a low cost. However, there are remaining challenges to be resolved in order to use the suggested catalytic materials, such as platinum (Pt), gold (Au), and palladium (Pd), due to their poor cost-effectiveness for device applications. In this study, to overcome these challenges, we suggest a useful method to increase the surface area of a noble metal catalyst material, resulting in a reduction of the total amount of catalyst usage. By employing block copolymer (BCP) self-assembly and nano-transfer printing (n-TP) processes, we successfully fabricated sub-20 nm Pt line and cross-bar patterns. Furthermore, we obtained a highly ordered Pt cross-bar pattern on a Ni thin film and a Pt-embedded Ni thin film, which can be used as hetero hybrid alloy catalyst structure. For a detailed analysis of the hybrid catalytic material, we used scanning electron microscope (SEM), transmission electron microscope (TEM) and energy-dispersive X-ray spectroscopy (EDS), which revealed a well-defined nanoporous Pt nanostructure on the Ni thin film. Based on these results, we expect that the successful hybridization of various catalytic nanostructures can be extended to other material systems and devices in the near future.

• Korean Journal of Environmental Agriculture
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• v.40 no.1
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• pp.1-12
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• 2021

BACKGROUND: G protein-coupled receptors (GPCRs) are widely distributed in various organisms. Insect GPCRs shown as in vertebrate GPCRs are membrane receptors that coordinate or involve in various physiological processes such as learning/memory, development, locomotion, circadian rhythm, reproduction, etc. This study aimed to identify GPCRs expressed in fat body and compare the expression pattern of GPCRs in different temperature conditions. METHODS AND RESULTS: To identify GPCRs genes and compare their expression in different temperature conditions, total RNAs of fat body in Plutella xylostella larva were extracted and the transcriptomes have been analyzed via next generation sequencing method. From the fat body transcriptomes, genes that belong to GPCR Family A, B, and F were identified such as opsin, gonadotropin-releasing hormone receptor, neuropeptide F (NPF) receptor, muthuselah (Mth), diuretic hormone receptor, frizzled, etc. Under low temperature, expressions of GPCRs such as C-C chemokine receptor (CCR), opsin, prolactin-releasing peptide receptor, substance K receptor, Mth-like receptor, diuretic hormone receptor, frizzled and stan were higher than those at 25℃. They are involved in immunity, feeding, movement, odorant recognition, diuresis, and development. In contrast to the control (25℃), at high temperature GPCRs including CCR, gonadotropin-releasing hormone receptor, moody, NPF receptor, neuropeptide B1 receptor, frizzled and stan revealed higher expression whose biological functions are related to immunity, blood-brain barrier formation, feeding, learning, and reproduction. CONCLUSION: Transcriptome of fat body can provide understanding the pools of GPCRs. Identifications of fat body GPCRs may contribute to develop new targets for the control of insect pests.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.5
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• pp.139-146
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• 2022

With the recent development of the Internet of Things (IoT) and the convergence of vehicles and IT technologies, high-performance applications such as autonomous driving are emerging, and multi-access edge computing (MEC) has attracted lots of attentions as next-generation technologies. In order to provide service to these computation-intensive tasks in low latency, many methods have been proposed to partition tasks so that they can be performed through cooperation of multiple MEC servers(MECSs). Conventional methods related to task partitioning have proposed methods for partitioning tasks on vehicles as mobile devices and offloading them to multiple MECSs, and methods for offloading them from vehicles to MECSs and then partitioning and migrating them to other MECSs. In this paper, the performance of task partitioning methods using offloading and migration is compared and analyzed in terms of service delay, blocking rate and energy consumption according to the method of selecting partitioning targets and the number of partitioning. As the number of partitioning increases, the performance of the service delay improves, but the performance of the blocking rate and energy consumption decreases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3565-3583
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• 2022

The task scheduling problem has received a lot of attention in recent years as a crucial area for research in the cloud environment. However, due to the difference in objectives considered by service providers and users, it has become a major challenge to resolve the conflicting interests of service providers and users while both can still take into account their respective objectives. Therefore, the task scheduling problem as a bi-objective game problem is formulated first, and then a task scheduling model based on the bi-objective game (TSBOG) is constructed. In this model, energy consumption and resource utilization, which are of concern to the service provider, and cost and task completion rate, which are of concern to the user, are calculated simultaneously. Furthermore, a many-objective evolutionary algorithm based on a partitioned collaborative selection strategy (MaOEA-PCS) has been developed to solve the TSBOG. The MaOEA-PCS can find a balance between population convergence and diversity by partitioning the objective space and selecting the best converging individuals from each region into the next generation. To balance the players' multiple objectives, a crossover and mutation operator based on dynamic games is proposed and applied to MaPEA-PCS as a player's strategy update mechanism. Finally, through a series of experiments, not only the effectiveness of the model compared to a normal many-objective model is demonstrated, but also the performance of MaOEA-PCS and the validity of DGame.

• Journal of Powder Materials
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• v.30 no.1
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• pp.22-28
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• 2023

The global demand for raw lithium materials is rapidly increasing, accompanied by the demand for lithiumion batteries for next-generation mobility. The batch-type method, which selectively separates and concentrates lithium from seawater rich in reserves, could be an alternative to mining, which is limited owing to low extraction rates. Therefore, research on selectively separating and concentrating lithium using an electrodialysis technique, which is reported to have a recovery rate 100 times faster than the conventional methods, is actively being conducted. In this study, a lithium ion selective membrane is prepared using lithium lanthanum titanate, an oxide-based solid electrolyte material, to extract lithium from seawater, and a large-area membrane manufacturing process is conducted to extract a large amount of lithium per unit time. Through the developed manufacturing process, a large-area membrane with a diameter of approximately 20 mm and relative density of 96% or more is manufactured. The lithium extraction behavior from seawater is predicted by measuring the ionic conductivity of the membrane through electrochemical analysis.

• Smart Media Journal
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• v.12 no.3
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• pp.49-59
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• 2023

Optical Camera Communication (OCC), known as the next-generation wireless communication technology, is currently under extensive research. The performance of OCC technology is affected by the communication environment, and various strategies are being studied to improve it. Among them, the most prominent method is applying convolutional neural networks (CNN) to the receiver of OCC using deep learning technology. However, in most studies, CNN is simply used to detect the transmitter. In this paper, we experiment with applying the convolutional neural network not only for transmitter detection but also for the Rx demodulation system. We hypothesize that, since the data images of the OCC system are relatively simple to classify compared to other image datasets, high accuracy results will appear in most CNN models. To prove this hypothesis, we designed and implemented an OCC system to collect data and applied it to 12 different CNN models for experimentation. The experimental results showed that not only high-performance CNN models with many parameters but also lightweight CNN models achieved an accuracy of over 99%. Through this, we confirmed the feasibility of applying the OCC system in real-time on mobile devices such as smartphones.

• Journal of Electrochemical Science and Technology
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• v.14 no.3
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• pp.293-300
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• 2023

The global energy storage markets have gravitated to high-energy-density and low cost of lithium-ion batteries (LIBs) as the predominant system for energy storage such as electric vehicles (EVs). High-Ni layered oxides are considered promising next-generation cathode materials for LIBs owing to their significant advantages in terms of high energy density. However, the practical application of high-Ni cathodes remains challenging, because of their structural and surface instability. Although extensive studies have been conducted to mitigate these inherent instabilities, a two-step process involving the synthesis of the cathode and a dry/wet coating is essential. This study evaluates a one-step β-Li₂SnO₃ layer coating on the surface of LiNi_0.8Co_0.2O₂ (NC82) via the thermal segregation of Sn owing to the solubility limit with respect to the synthesis temperature. The doping, segregation, and phase transition of Sn were systematically revealed by structural analyses. Moreover, surface-engineered 5 mol% Sn-coated LiNi_0.8Co_0.2O₂ (NC82_Sn5%) exhibited superior capacity retention compared to bare NC82 owing to the stable surface coating layer. Thus, the developed one-step coating method is suitable for improving the properties of high-Ni layered oxide cathode materials for application in LIBs.