• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.789-795
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• 2023

Digital-Twin are recognized as an important core technology for the realization of Smart Factories by simulating and optimizing the monitoring and predictive maintenance of manufacturing equipment and the operation of production lines in a digital space. To implement this system, we adopt the IEC62541-based OPC-UA (Open Platform Communications Unified-Architecture) Protocol, which has strengths in interoperability and connectivity between heterogeneous platforms. Therefore, In this paper, We designed and implemented an IIoT(Industry Internet of Things) system that connects heterogeneous platforms, and developed an OPC-UA simulator based on IEC 62541. We will present whether the data will be applied to the Digital-Twin Platform and whether it will work, and proceed with performance tests and evaluations. We evaluate the operation performance and OPC-UA performance of the Digital-Twin platform lightened by the proposed device, and present the optimal IEC62514-based simulator system. We proceeded with the performance evaluation of sending and receiving data with OPC-UA wrapping with the proposed simulator, and found that a lightweight Digital-Twin platform can be operated. This research can apply the OPC-UA protocol for implementing smart factory and meta-factory in the manufacturing shop floor with limited resources, avoiding the waste of time and space on the shop floor through the OPC-UA simulator. We expect that this will contribute to a significant improvement in efficiency by minimizing.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.29-35
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• 2023

Braille can be said to be an essential means used for the visually impaired to communicate or acquire information on visual materials in their lives. However, the rate of interpretation of braille among the visually impaired is insignificant at 5%. As a result, libraries for the visually impaired produce various types of materials that can obtain various information for the visually impaired and also have assistive technology equipment to interpret them. However, the publication rate of Braille books is too low to purchase and interpret Braille books. In addition, the Braille interpretation rate is too low, and the purchase of assistive technology devices is too expensive and slow. Therefore, in this paper, we implemented a system that displays Braille using Arduino to help visually impaired people in addition to the existing methods they use to obtain information. For Braille display, Korean data is transmitted from Python through serial communication between Python and Arduino, and Arduino, which receives the data, compares the Korean data with the data in the array in the program and retrieves the Braille values of the Korean data. Here, the Braille value was expressed by controlling the servo motor perpendicular or horizontal to the body using white and black circles based on the Braille list.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1185-1193
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• 2023

The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.23-28
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• 2023

Windows operating system generates various logs with timestamps. Timestamp tampering is an act of anti-forensics in which a suspect manipulates the timestamps of data related to a crime to conceal traces, making it difficult for analysts to reconstruct the situation of the incident. This can delay investigations or lead to the failure of obtaining crucial digital evidence. Therefore, various techniques have been developed to detect timestamp tampering. However, there is a limitation in detection if a suspect is aware of timestamp patterns and manipulates timestamps skillfully or alters system artifacts used in timestamp tampering detection. In this paper, a method is designed to detect changes in timestamps, even if a suspect alters the timestamp of a file on a storage device, it is challenging to do so with precision beyond millisecond order. In the proposed detection method, the first step involves verifying the timestamp of a file suspected of tampering to determine its write time. Subsequently, the confirmed time is compared with the file size recorded within that time, taking into consideration the performance of the storage device. Finally, the total capacity of files written at a specific time is calculated, and this is compared with the maximum input and output performance of the storage device to detect any potential file tampering.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.967-971
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• 2023

Recently, a variety of AI-based platform services are available, and one of them is ChatGPT that processes a large quantity of data in the natural language and generates an answer after self-learning. ChatGPT can perform various tasks including software programming in the IT sector. Particularly, it may help generate a simple program and correct errors using C Language, which is a major programming language. Accordingly, it is expected that ChatGPT is capable of effectively using Verilog HDL, which is a hardware language created in C Language. Verilog HDL synthesis, however, is to generate imperative sentences in a logical circuit form and thus it needs to be verified whether the products are executed properly. In this paper, we aim to select small-scale logical circuits for ease of experimentation and to verify the results of circuits generated by ChatGPT and human-designed circuits. As to experimental environments, Xilinx ISE 14.7 was used for module modeling, and the xc3s1000 FPGA chip was used for module embodiment. Comparative analysis was performed on the use area and processing time of FPGA to compare the performance of ChatGPT products and Verilog HDL products.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.137-148
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• 2024

The purpose of this study is to determine how the use of retailtech technology affects consumers' purchase intention. Furthermore, this study aims to investigate the mediating effects of technology usefulness and ease of use on this influence relationship and whether experiential marketing moderates consumers' purchase intention. The survey was conducted from August 1, 2023 to September 30, 2023, and a total of 257 people participated in the study. For statistical analysis, hierarchical regression analysis, three-stage mediation regression analysis, and hierarchical three-stage controlled regression analysis were conducted to test the hypothesis. The results of the study are as follows. First, it was confirmed that big data-AI utilization, mobile-SNS utilization, live commerce utilization, and IoT utilization affect purchase intention in retail technology utilization. Second, technology usefulness has a mediating effect on IoT utilization, mobile-SNS utilization, and big data-AI utilization. Third, perceived ease of use of technology mediated the effects of IoT utilization, mobile-SNS utilization, live-commerce utilization, and big data-AI utilization. Fourth, escapist experience has a moderating effect on mobile SNS utilization and live commerce utilization. Fifth, esthetic experience has a moderating effect on mobile-SNS utilization and big data-AI utilization. Through this study, we hope that the domestic distribution industry will contribute to national competitiveness by securing the competitive advantage of companies by utilizing new technologies in entering the global market.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.207-212
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• 2024

The importance of hydrogen fuel cells continues to be emphasized, and there is a growing demand for education and training in this field. Among various educational environments, metaverse education is opening a new era of change in the global education industry, especially to adapt to remote learning. The most significant change that the metaverse has brought to education is the shift from one-way, instructor-centered, and static teaching approaches to multi-directional and dynamic ones. It is expected that the metaverse can be effectively utilized in hydrogen fuel cell engineer education, not only enhancing the effectiveness of education by enabling learning and training anytime, anywhere but also reducing costs associated with engineering education.In this research, inspired by these ideas, we are designing a fuel cell education platform. We have created a platform that combines theoretical and practical training using the metaverse. Key aspects of this research include the development of educational training content to increase learner engagement, the configuration of user interfaces for improved usability, the creation of environments for interacting with objects in the virtual world, and support for convergence services in the form of digital twins.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.137-142
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• 2024

Recently, deep learning technology has become those methods as de facto standards in the area of medical data representation. But, deep learning inherently requires a large amount of training data, which poses a challenge for its direct application in the medical field where acquiring large-scale data is not straightforward. Additionally, brain signal modalities also suffer from these problems owing to the high variability. Research has focused on designing deep neural network structures capable of effectively extracting spectro-spatio-temporal characteristics of brain signals, or employing self-supervised learning methods to pre-learn the neurophysiological features of brain signals. This paper analyzes methodologies used to handle small-scale data in emerging fields such as brain-computer interfaces and brain signal-based state prediction, presenting future directions for these technologies. At first, this paper examines deep neural network structures for representing brain signals, then analyzes self-supervised learning methodologies aimed at efficiently learning the characteristics of brain signals. Finally, the paper discusses key insights and future directions for deep learning-based brain signal analysis.

• Journal of Practical Engineering Education
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• v.16 no.3_spc
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• pp.259-265
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• 2024

In order to improve the SW convergence capabilities of university undergraduate students, methods to evaluate undergraduate students' code design capabilities should be researched along with the development of related courses. In previous studies, there were qualitative evaluation methods and quantitative relative evaluation methods for code results. In the quantitative relative evaluation method, the number of problem decomposition depth, number of function reuses, and number of functions were measured and evaluated. In this study, an evaluation method that was not presented in previous studies was proposed using the problem of presenting the number of input and output information types when designing code. The evaluation problems proposed in this paper applied up to three types of input information and three types of output information. Through this, five code design evaluation questions were presented and a method to quantitatively calculate code design scores was proposed. Codes from 100 student respondents were collected and analyzed through courses that applied the proposed evaluation method. Through result analysis, the number of problem decomposition depths was proportional to the number of types of input information, the number of function reuses was proportional to the number of types of output information, and the number of functions showed a correlation that was proportional to the total number of types of input and output information. Lastly, by analyzing the distribution of evaluation scores of 100 respondents, we demonstrated that the code design evaluation method according to the five input/output information condition evaluation problems is effective.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.232-243
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• 2024

Purpose: Recently, large-scale forest fires caused by climate change, natural disasters, and human factors have been increasing every year in the East Coast and Taebaek Mountains region. Although forest fire extinguishing using helicopters is currently increasing, the need to introduce air force transport aircraft has continued to be raised due to the importance of early fire extinguishment to respond to large forest fires and the difficulty of extinguishing forest fires between sheep. This study seeks to present a plan for developing a post-fire management system for several aspects - achieving operational objectives, overcoming the operating environment, selecting a staging area, and efficient operation measures - to efficiently perform forest fire extinguishing missions using Air Force transport aircraft. Method: Based on literature research on forest fire extinguishing, forest fire extinguishing experiments using fixed-wing aircraft, and the operation status and operation method of forest fire extinguishing helicopters, the pros and cons of helicopter operation and the effects of large forest fire extinguishing using a large transport aircraft (C-130) Analyze the effectiveness of operation through analysis. Results: When extinguishing a large forest fire, an effective CM (Consequence Management) application plan was derived, including effective operation, control, command system, dispatch request, and forest fire extinguishment when integrating helicopter and fixed-wing aircraft (C-130). Conclusion: The application of the concept of CM (Consequence Management) is partially applied to some areas of chemical, biological, and radiological (CBRNE) protection in Korea, but efficient operation, control, and command systems are established when integrated operation of helicopters and large aircraft (C-130) in forest fire extinguishment. the concept of CM (Consequence Management), which is operated in advanced countries, was applied for safety management, dispatch requests, and forest fire extinguishing, thereby contributing to the establishment of a more advanced disaster and post-disaster management system.