• Journal of the Korea Society for Simulation
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• v.28 no.2
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• pp.169-177
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• 2019

LVC(Live-Virtual-Constructive) training system is drawing attention due to changes in battlefield situation and the development of advanced information and communication technologies. The ROKAF(Republic of Korea Air Force) plans to construct LVC training system capable of scientific training. This paper analyzes the results of V-C interoperability test with three fighter simulators as virtual systems and a theater-level wargame model as a constructive system. The F-15K, KF-16, and FA-50 fighter simulators, which have different interoperable methods, were converted into a standard for simulation interoperability. Using the integrated field environment simulator, the fighter simulators established a mutually interoperable environment. In addition, the Changgong model, which is the representative training model of the Air Force, was converted to the standard for simulation interoperability, and the integrated model was implemented with optimized interoperability performance. Throughput experiments, It was confirmed that the fighter simulators and the war game model of the ROKAF could be interoperable with each other. The results of this study are expected to be a good reference for the future study of the ROKAF LVC training system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.378-381
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• 2019

In this study, we compared the perception of general and specialist teachers about the software education that entered the classroom by the 2015 revised curriculum. For the comparison of cognition, the 17 - hour hourly curriculum, the statement of achievement criteria, and the curriculum were organized in grades 5-6, but the appropriateness of the inclusion of only textbooks in grade 6 was questioned. The general teacher had many opinions that all three items are appropriate. On the other hand, professional teachers were inadequate and many were. It is necessary to provide various opportunities such as the training for the recognition change in the future. In addition, positive keywords for the introduction of general and specialist teachers were derived as a result of analyzing the main keywords of the free - response opinions about the introduction of educational robots in the practical course curriculum and textbooks. However, general teachers showed differences in the use of post - adoption education, such as passive and passive keywords such as support, difficulty, and problems, and the use of specialist teachers and education. In the future, it seems that it is necessary to provide teaching support to elementary school teachers, to provide beginner level difficulty training.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.259-264
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• 2019

This paper proposes an image prediction system architecture for deep running in enterprise environment. Easily transform into an artificial intelligence platform for an enterprise environment, and allow sufficient deep-running services to be developed and modified even in Java-centric architectures to improve the shortcomings of Java-centric enterprise development because artificial intelligence platforms are concentrated in the pipeline. In addition, based on the proposed environment, we propose a more accurate prediction system in the deep running architecture environment that has been previously learned through image forecasting experiments. Experiments show 95.23% accuracy in the image example provided for deep running to be performed, and the proposed model shows 96.54% accuracy compared to other similar models.

• Journal of Industrial Convergence
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• v.18 no.6
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• pp.19-25
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• 2020

Big data analytics are indispensable today in various industries and public sectors. Therefore, in this study, we will utilize big data analysis to search for improvement plans for domestic tourism services using the LDA analysis method. In particular, we have tried an exploratory approach that can improve tourist satisfaction, which can improve revisit and service, especially in Seoul, which has the largest number of foreign tourists. In this study, we collected and analyzed statistical data of Seoul City and Korea Tourism Organization and Internet information such as SNS via R. And we utilized text mining methods including LDA. As a result of the analysis, one of the purposes of visiting South Korea by foreigners was gastronomic tourism. We will try to derive measures to improve the quality of services centered on gastronomic tourism.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.519-526
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• 2022

Basically, autonomous vehicles drive using road and traffic information collected by various sensors. However, it is known that there is a limitation to realizing fully autonomous driving with only such technologies and information. In recent, various efforts are being made to overcome the limitations of sensor-based autonomous driving, and efforts are also underway to utilize more specific and accurate road and traffic information, called local dynamic map (LDM). However, LDM-related data standards and specifications have not yet been sufficiently verified, and research on the spatiotemporal scope of LDM during autonomous driving is extremely limited. Based on this background, the purpose of this study is to identify these limitations through an analysis of previous LDM-related studies and to present a framework for calculating the spatiotemporal activation section of LDM-based road and traffic information.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.23-35
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• 2023

Korea Augmentation Satellite System (KASS) is a satellite-based augmentation system (SBAS) that provides approach procedure with vertical guidance-I (APV-I) level corrections and integrity information to Korea territory. KASS is used to monitor navigation performance in real-time, and this paper introduces the design, implementation, and verification process of mission monitoring (MIMO) in KASS. MIMO was developed in compliance with the Minimum Operational Performance Standards of the Radio Technical Commission for Aeronautics for Global Positioning System (GPS)/SBAS airborne equipment. In this study, the MIMO system was verified by comparing and analyzing the outputs of reference tools. Additionally, the definition and derivation method of accuracy, integrity, continuity, and availability subject to MIMO were examined. The internal and external interfaces and functions were then designed and implemented. The GPS data pre-processing was minimized during the implementation to evaluate the navigation performance experienced by general users. Subsequently, tests and verification methods were used to compare the obtained results based on reference tools. The test was performed using the KASS dataset, which included GPS and SBAS observations. The decoding performance of the developed MIMO was identical to that of the reference tools. Additionally, the navigation performance was verified by confirming the similarity in trends. As MIMO is a component of KASS used for real-time monitoring of the navigation performance of SBAS, the KASS operator can identify whether an abnormality exists in the navigation performance in real-time. Moreover, the preliminary identification of the abnormal point during the post-processing of data can improve operational efficiency.

• Journal of Industrial Convergence
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• v.19 no.6
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• pp.59-66
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• 2021

Globally, the prolonged pandemic of COVID-19 (COVID-19) has had a great impact on all industries. In particular, in the field of education, online classes (non-face-to-face) had some negative perceptions of online classes, such as lack of preparation for learning and student dissatisfaction with the class. According to the current situation survey in 2020, non-face-to-face classes accounted for about 56% of the class, and streaming real-time classes and video content-based classes accounted for most of the class. This study empirically analyzes the problems to be solved by online classes through the 2020-2021 survey (software application practical class university students), and explains the detailed program and development plan (implementation result). This study intends to contribute to the development of online learning development of each educational institution after the end of the corona crisis.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.2
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• pp.81-86
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• 2022

Given that time series are used in various fields, such as finance, IoT, and manufacturing, data analytical methods for accurate time-series forecasting can serve to increase operational efficiency. Among time-series analysis methods, multi-horizon forecasting provides a better understanding of data because it can extract meaningful statistics and other characteristics of the entire time-series. Furthermore, time-series data with exogenous information can be accurately predicted by using multi-horizon forecasting methods. However, traditional deep learning-based models for time-series do not account for the heterogeneity of inputs. We proposed an improved time-series predicting method, called the temporal fusion transformer method, which combines multi-horizon forecasting with interpretable insights into temporal dynamics. Various real-world data such as stock prices, fine dust concentrates and electricity consumption were considered in experiments. Experimental results showed that our temporal fusion transformer method has better time-series forecasting performance than existing models.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.563-570
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• 2023

The Safety Transmission Unit(STU) is a critical device used in railway systems to ensure safe and efficient operations by providing communication between trains and railway infrastructure. It is responsible for transmitting vital information and commands, allowing for the control and coordination of train movements. The STU plays a crucial role in maintaining the safety of passengers, crew, and the overall railway network. This paper presents the design and testing of a STU for the next-generation wireless-based train control system. An analysis of european and domestic standards was conducted to review requirements and ensure the design of a STU for the train control system meets international standards. Based on this analysis, hardware and software designs were developed to create an internationally recognized level of safety for the communication device. To verify the functionality of the STU, a simulator was developed, and it was confirmed that the designed features were successfully implemented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.186-188
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• 2021

The architecture named IDPS is a design concept of web-based integrated platform for heterogeneous naval combat system, which accomplishes efficiency(decreasing complexity) of diagnosis process and reduces time to diagnose system. Each type of surface vessel has its own diagnostic processes and applications, and that means it also requires its own diagnostic engineer(inefficiency in human resource management). In addition, man-based diagnostic causes quality issues such as difference approach of log analysis in accordance with engineer skills. Thus In this paper, we designed integrated diagnostic platform named IDPS with simplified common process regardless of type of surface vessel and we reinforced IDPS with status decision algorithm(SDA) that judges current software status of vessel based on gathered lots of logs. It will enable engineers to diagnose system more efficiently and to use more resources in utilizing SDA-analyzed diagnostic results.