• Journal of Industrial Technology
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• v.42 no.1
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• pp.1-5
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• 2022

Although the mileage of electric vehicles can be increased based on the excellent energy density of the LiNi_0.9Co_0.05Mn_0.05O₂, it is known that the reason for limiting its use is the low lifespan and poor surface stability due to the structural deformation of the LiNi_0.9Co_0.05Mn_0.05O₂. To improve the structural stability of LiNi_0.9Co_0.05Mn_0.05O₂, electrochemical performance is improved by La coating on the surface. La-modified LiNi_0.9Co_0.05Mn_0.05O₂ shows an initial capacity of 210.6 mAh/g, a capacity retention rate of 89.9 % after 50 cycles, and a retention rate of 52.5% at 6.0 C. These are superior performances than the pristine sample, because the structural stability of the LiNi_0.9Co_0.05Mn_0.05O₂ cathode is improved by the La coating.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.101-107
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• 2022

Modeling and simulation is a technique used for operational verification, performance analysis, operational optimization, and prediction of target systems. Discrete Event System Specification (DEVS) of this representative technology defines models with a strict formalism and stratifies the structures between the models. When the atomic DEVS models operate with an intention different the target system, the simulation may lead to erroneous decision-making. However, most DEVS systems have the exclusion of the model test or provision of the manual test, so developers spend a lot of time verifying the atomic models. In this paper, we propose a script-based automated test system for accurate and fast validation of atomic models in Python-based DEVS. The proposed system uses both the existing method of manual testing and the new method of the script-based testing. As Experimental results in our system, the script-based test method was executed within 24 millisecond when the script was executed 10 times consecutively. Thus, the proposed system guarantees a fast verification time of the atomic models in our script-based test and improves the reusability of the test script.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.59-63
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• 2022

In recent years, research on smart factory wireless mobile communication technology that wirelessly remotely controls utilities is being actively conducted. The Wi-SUN(Wireless Smart Utility Network) Alliance proposed Wi-SUN protocol structure suitable for building a platform such as a smart factory as a new wireless communication standardization standard based on EEE802.15.4g/e. It analyzes the performance of the IEEE802.15.4e CSL(Coordinated Sampled Listening) Mode MAC(Media Access Control) in terms of power consumption and looks at considerations for efficient operation. Although CSL-MAC can dramatically reduce power consumption at the receiving end in an asynchronous manner, it has been found that the transmitting end has a disadvantage in that power consumption occurs due to an excessive wake-up sequence.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.409-416
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• 2022

This paper relates to the blind noise separation method of time-delayed convolutive mixed signals. Since the mixed model of acoustic signals in a closed space is multi-channel, a convolutive blind signal separation method is applied and time-delayed data samples of the two microphone input signals is used. For signal separation, the mixing coefficient is calculated using an inverse model rather than directly calculating the separation coefficient, and the coefficient update is performed by repeated calculations based on secondary statistical properties to estimate the speech signal. Many simulations were performed to verify the performance of the proposed blind signal separation. As a result of the simulation, noise separation using this method operates safely regardless of convolutive mixing, and PESQ is improved by 0.3 points compared to the general adaptive FIR filter structure.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.129-137
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• 2010

Currently used shortest path search algorithms involve graphs with vertices and weighted edges between each vertex. However, when finding the shortest path with a randomly shaped obstacle(an island, for instance) positioned in between the starting point and the destination, using such algorithms involves high memory inefficiency and is significantly time consuming - all positions in the map should be considered as vertices and every line connecting any of the two adjacent vertices should be considered an edge. Therefore, we propose a new method for finding the shortest path in such conditions without using weighted graphs. This algorithm will allow finding the shortest obstacle bypass given only the positions of the obstacle boundary, the starting point and the destination. When the row and column size of the minimum boundary rectangle to include an obstacle is m and n, respectively, the proposed algorithm has the maximum time complexity, O(mn). This performance shows the proposed algorithm is very efficient comparing with the currently used algorithms.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.1-13
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• 2023

As federated learning brings a large paradigm to modern artificial intelligence research, efforts are being made to incorporate federated learning into research in various fields. However, researchers who apply federated learning face the problem of choosing a federated learning framework and benchmark tool suitable for their situation and purpose. This study aims to present guidelines for selection of federated learning frameworks and benchmark tools considering the circumstances of researchers who apply federated learning in practice. In particular, there are three main contributions in this study. First, it generalizes the situation of the researcher applying federated learning by combining it with the goal of federated learning and proposes guidelines for selecting a federated learning framework suitable for each situation. Second, it shows the suitability of selection by comparing the characteristics and performance of each federated learning framework to the researcher. Finally, the limitations of the existing federated learning framework and a plan for real-world federated learning operation are proposed.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.483-494
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• 2023

Recently, gas turbine generators are widely used for frequency control of power systems. Although the inlet temperature of a gas turbine is a key factor related to the performance and lifespan of the device, the inlet temperature is not measured directly for reasons such as the turbine structure and operating environment. In particular, the inlet temperature of the reheating gas turbine is very important for stable operation management, but field workers are experiencing a lot of difficulties because the manufacturer does not provide information on the calculation formula. Therefore, in this study, we propose a method for estimating the inlet temperature of a gas turbine using a machine learning-based linear regression analysis method based on a polytropic process equation. In addition, by proposing an inlet temperature calculation algorithm through the usefulness analysis and verification of the inlet temperature calculation model obtained through linear regression analysis, it is intended to help to improve the level of reheat gas turbine combustion tuning technology.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.2
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• pp.97-103
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• 2023

Since most of the information is transmitted through the network, eavesdropping and interception by a third party may occur. Appropriate measures are required for effective, secure and confidential communication in the network. Steganography is a technology that prevents third parties from detecting that confidential information is hidden in other media. Due to structural vulnerabilities, information protected by encryption and steganography techniques can be easily exposed to illegitimate groups. In order to improve the limitations of LSB where the simplicity and predictability of the hiding method exist, I propose a technique to improve the security of the message to be hidden based on PRNG and recursive function. To enhance security and confusion, XOR operation was performed on the result of selecting a random bit from the upper bits of the selected channel and the information transformed by the RS-box. PSNR and SSIM were used to confirm the performance of the proposed method. Compared to the reference values, the SSIM and PSNR of the proposed method were 0.9999 and 51.366, respectively, confirming that they were appropriate for hiding information.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.81-88
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• 2022

The major educational goal of reading part, which occupies important portion in Korean language in Korean SAT, is to evaluated whether a given text can be fully understood. Therefore given questions in the exam must be able to solely solvable by given text. In this paper we developed a datatset based on Korean SAT's reading part in order to evaluate whether a deep learning language model can classify if the given question is true or false, which is a binary classification task in NLP. In result, by applying language model solely according to the passages in the dataset, we were able to acquire better performance than 59.2% in F1 score for human performance in most of language models, that KoELECTRA scored 62.49% in our experiment. Also we proved that structural limit of language models can be eased by adjusting data preprocess.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.177-186
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• 2017

Recently, Autonomous vehicles are getting hot attention. Amazon, the biggest online shopping service provider is developing a delivery system that uses drones. This kinds of platforms are need accurate attitude information for navigation. In this paper, a structure design of AHRS using low-cost inertia sensor is proposed. To estimate attitudes a Kalman filter which uses a quaternion based dynamic model, bias-removed measurements from MEMS Gyro, raw measurements from MEMS accelerometer and magnetometer, is designed. To remove bias from MEMS Gyro, an additional Kalman filter which uses raw Gyro measurements and attitude estimates, is designed. The performance of implemented AHRS is compared with high price off-the-shelf 3DM-GX3-25 AHRS from Microstrain. The Gyro bias was estimated within 0.0001[deg/s]. And from the estimated attitude, roll and pitch angle error is smaller than 0.2 and 0.3 degree. Yaw angle error is smaller than 6 degree.