• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.9-16
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• 2022

In this paper, we propose a plan to design and utilize the RDBS(Record Block Data file management System) so that data can be recovered when data files in the Combat Management System are mismatched. The CMS(Combat Management System) manages the same files in multiple IPN(Infomation Processing Node) repositories to support multiplexing. However, mismatches in data files can occur due to equipment maintenance or user immaturity. The existing CMS does not manage the history of changes in data files, and when a mismatch occurs, data file were synchronized based on the latest date. But, It is difficult to say that files with the latest date have the highest reliability, and once the file synchronization has progressed, it cannot be recovered with pre-synchronization data. To solve this problem, data was stored and synchronized in units of record blocks using RDBS proposed in this paper, and the Rsync algorithm was used to reduce the overhead of file synchronization due to units of record blocks. SW applied with RDBS was tested for performance in a simulated environment, and it was confirmed that it could be applied to CMS through normal operation confirmation.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.193-206
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• 2021

Artificial Intelligence (AI) has been inserted into people's lives through Intelligent Virtual Assistants (IVA), like Alexa. Moreover, intelligent systems have expanded to design studios. This research delves into designers' perspectives on developing AI-based practices and examines the challenges of adopting future intelligent design assistants. We surveyed UX/UI professionals in Brazil to understand how they use IVAs and AI design tools. We also explored a scenario featuring the use of Alexa Sensei, a hypothetical voice-controlled AI-based design assistant mixing Alexa and Adobe Sensei characteristics. The findings indicate respondents have had limited opportunities to work with AI, but they expect intelligent systems to improve the efficiency of the design process. Further, majority of the respondents predicted that they would be able to collaborate creatively with AI design systems. Although designers anticipated challenges in natural language interaction, those who already adopted IVAs were less resistant to the idea of working with Alexa Sensei as an AI design assistant.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.11-17
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• 2022

In this paper, a model that can increase the efficiency of work in arranging interior furniture by applying augmented reality technology was studied. In the existing system to which augmented reality is currently applied, there is a problem in that information is limitedly provided depending on the size and nature of the company's product when outputting the image of furniture. To solve this problem, this paper presents an AR labeling algorithm. The AR labeling algorithm extracts feature points from the captured images and builds a database including indoor location information. A method of detecting and learning the location data of furniture in an indoor space was adopted using the CNN technique. Through the learned result, it is confirmed that the error between the indoor location and the location shown by learning can be significantly reduced. In addition, a study was conducted to allow users to easily place desired furniture through augmented reality by receiving detailed information about furniture along with accurate image extraction of furniture. As a result of the study, the accuracy and loss rate of the model were found to be 99% and 0.026, indicating the significance of this study by securing reliability. The results of this study are expected to satisfy consumers' satisfaction and purchase desires by accurately arranging desired furniture indoors through the design and implementation of AR labels.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.6
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• pp.631-638
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• 2022

Microgrid, which enables the production and consumption of electricity to be done independently on a small scale, has been studied on one of the solutions of reinforcement for flexibility of electronic system. This study examined the application effect of new microgrid by applying hybrid battery in electric power storage device. We designed the system to highlight the advantage of each battery and complement the disadvantage by using hybrid system with Lithium-ion battery and interval Redox flow battery. It runs with lithium-ion battery during the initial startup while the Redox flow battery operates for a long time at the end of excessive period, and it enables a discharge of Lithium-ion and Redox flow battery at the same time when the load has a large output. We chose Maldives as a subject of this study for organizing and optimizing independent microgrid. Maldives is the country to accomplish 100% domestic electricity in South Asia, but the whole electric power is supplied through diesel generation imported fossil fuel. We organized and optimized microgrid for energy independence on Malahini island to solve Maldives energy cost problem and global energy environment matters. We analyzed the daily power supply and accumulated the power supply from September 18, 2018~February 11, 2019. The accumulated power supply was about 120.4 MWh and the daily power supply was about 800~1000 kWh. Based on the collected information, we divided the cases into three models which are only diesel generator, solar generator as well as diesel generator, and solar+ESS+diesel generator. We analyzed the amount of oil consumption compared to the cost of construction and power output. The result showed that solar+ESS+diesel generator was most economically feasible. As well, we obtained that our considering hybrid battery system reduced the fuel consumption for diesel power generation about 10~15%.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.267-274
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• 2022

The purpose of this study is to investigate the learning satisfaction and perception of the students who have taken the online classes of the Digital Innovation Sharing University in the field of new energy industry, and to analyze the relationship between the learning satisfaction and core competencies. In order to achieve this purpose, the results of the learning satisfaction survey of a total of 470 students who took the digital innovation sharing university classes in the new energy industry were analyzed in both quantitative and qualitative methods. As a result of quantitative analysis, students' learning satisfaction was generally above average, and they were particularly satisfied with the setting and operation of educational goals. In addition, it was found that students' learning satisfaction had a statistically significant effect on students' core competencies. As a result of the qualitative analysis, it was possible to confirm the direction of improvement of the curriculum in the areas of function, operation, and content. Based on the results of this study, it is expected that the digital innovation sharing university curriculum quality management feedback system will be prepared in the future, and it will be the foundation for the continuous establishment of the curriculum quality management system.

• Journal of Korean Library and Information Science Society
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• v.53 no.3
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• pp.263-285
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• 2022

This study presented the factor analysis on constructing the new factors affecting the middle school students' online learning behaviors from the questionnaires employed among middle school students. A total of 204 students participated and the data were collected in South Korea. The sample of middle school ninth-grade students was selected and used through purposive sampling. Findings from the factor analysis provided evidence for the eight-factor solution for the 35-items accounting for 66.15% of the shared variance. A wide range of factors has been considered to identify students' online learning behaviors. The appropriate experience and use of e-learning in the middle school period is also important as it will be a critical stepstone for future education. This research provides information that has been taken into account for advancing online learning to enhance the quality of e-learning systems for middle school students. The study results provided eight new factors affecting the middle school students' online learning behaviors; that is 1) communication using social media as a learning tool, 2) intention to share information using ICT, 3) addiction of technology, 4) adoption of technology, 5) seeking information using ICT, 6) use of social media learning, 7) information search using ICT, and 8) immersion of technology. This study confirmed that middle school students prefer communication using social media as a learning tool, and value intention to share information using ICT for the most part. The data obtained based on factor analysis can highlight the online learning behaviors towards a mixture of social media learning and ICT to ensure a new educational platform for the future of e-learning. This research expects to be useful for both middle schools of online learning to better understand students' online learning behaviors and design online learning environments and information professionals to better assist students who particularly need digital literacy.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.233-247
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• 2023

Recently, research on detecting objects in hidden spaces beyond the direct line-of-sight of observers has received attention. Most studies use optical equipment that utilizes the directional of light, but sound that has both diffraction and directional is also suitable for non-line-of-sight(NLOS) research. In this paper, we propose a novel method of detecting objects in non-line-of-sight (NLOS) areas using acoustic signals in the audible frequency range. We developed a deep learning model that extracts information from the NLOS area by inputting only acoustic signals and predicts the properties and location of hidden objects. Additionally, for the training and evaluation of the deep learning model, we collected data by varying the signal transmission and reception location for a total of 11 objects. We show that the deep learning model demonstrates outstanding performance in detecting objects in the NLOS area using acoustic signals. We observed that the performance decreases as the distance between the signal collection location and the reflecting wall, and the performance improves through the combination of signals collected from multiple locations. Finally, we propose the optimal conditions for detecting objects in the NLOS area using acoustic signals.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.6
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• pp.181-188
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• 2023

Block cipher is not expected to be safe for quantum computer, as Grover's algorithm reduces the security strength by accelerating brute-force attacks on symmetric key ciphers. So it is necessary to check the post-quantum security strength by implementing quantum circuit for the target cipher. In this paper, we propose the optimal quantum circuit implementation result designed as a technique to minimize the use of quantum resources (qubits, quantum gates) for SIMECK lightweight cryptography, and explain the operation of each quantum circuit. The implemented SIMECK quantum circuit is used to check the estimation result of quantum resources and calculate the Grover attack cost. Finally, the post-quantum strength of SIMECK lightweight cryptography is evaluated. As a result of post-quantum security strength evaluation, all SIMECK family cipher failed to reach NIST security strength. Therefore, it is expected that the safety of SIMECK cipher is unclear when large-scale quantum computers appear. About this, it is judged that it would be appropriate to increase the block size, the number of rounds, and the key length to increase the security strength.

• Journal of the Korean GEO-environmental Society
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• v.24 no.9
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• pp.33-40
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• 2023

The lateral load which is applied to the pile foundation supporting the superstructure during an earthquake is divided into the inertia force of the upper structure and the kinematic force of the ground. The inertia force and the kinematic force could cause failure to the pile foundation through different complex mechanisms. So it is necessary to predict and evaluate interaction of the ground-pile-structure properly for the seismic design of the foundation. The interaction is affected by the lateral behavior of the structure, the length of the pile, the boundary conditions of the head, and the relative density of the ground. Confining pressure and ground stiffness change accordingly when the relative density changes, and it results that the coefficient of subgrade reaction varies depending on each system. Horizontal bearing behavior and capacity of the pile foundation vary depending on lateral load condition and relative density of the sandy soil. Therefore, the 1g shaking table tests were conducted to confirm the effect of the relative density of the dried sandy soil to dynamic behavior of the group pile supporting the superstructure. The result shows that, as the relative density increases, maximum acceleration of the superstructure and the pile cap increases and decreases respectively, and the slope of the p-y curve of the pile decreases.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.4
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• pp.273-282
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• 2023

Probabilistic safety assessment (PSA) has been widely used to evaluate the seismic risk of nuclear power plants (NPPs). However, studies on seismic PSA for process plants, such as gas plants, oil refineries, and chemical plants, have been scarce. This is because the major disasters to which these process plants are vulnerable include explosions, fires, and release (or dispersion) of toxic chemicals. However, seismic PSA is essential for the plants located in regions with significant earthquake risks. Seismic PSA entails probabilistic seismic hazard analysis (PSHA), event tree analysis (ETA), fault tree analysis (FTA), and fragility analysis for the structures and essential equipment items. Among those analyses, ETA can depict the accident sequence for core damage, which is the worst disaster and top event concerning NPPs. However, there is no general top event with regard to process plants. Therefore, PSA cannot be directly applied to process plants. Moreover, there is a paucity of studies on developing fragility curves for various equipment. This paper introduces PSA for gas plants based on FTA, which is then transformed into Bayesian network, that is, a probabilistic graph model that can aid risk-informed decision-making. Finally, the proposed method is applied to a gas plant, and several decision-making cases are demonstrated.