• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.539-544
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• 2021

The tactical data link is a military data network to improve the ability to recognize battlefield situations. The ROK military is promoting the tactical data link performance improvement programs. Tactical data link is essential to combine and integrate various platforms, sensor data, and command and control (C2) systems. Therefore, the research on related technical fields is required. However, the tactical data link has not disclosed detailed technical information due to the characteristics of military operation. In this paper, we propose a data-based automated analysis methodology using intellectual property information to understand the technology trend of tactical data link. In this paper, data related to intellectual property is automatically collected and pre-processed, and analyzed in terms of time series. In addition, the current status of each institution of patent technology information was generated, and the process of identifying key-researchers through network analysis was presented with providing results of our approach in this paper.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.17-22
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• 2021

In this paper, a machine learning-based automatic infographic recommendation system is proposed to improve the existing infographic production method. This system consists of a part that machine learning multiple infographic images and a part that automatically recommends infographics with artificial intelligence only by inputting basic data from the user. The recommended infographics are provided in the form of a library, and additional data can be input by drag & drop method. In addition, the infographic image is designed to be dynamically adjusted according to the size of the input data. As a result of analyzing the machine learning-based automatic infographic recommendation process, the matching success rate for layout and keyword was very high, and the matching success rate for type was rather low. In the future, a study to improve the matching success rate for the image type for each part of the infographic will be needed.

• Journal of IKEEE
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• v.26 no.3
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• pp.416-421
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• 2022

In this study, we present a fully automated system that combines camera technology with liquid crystal technology to create a polarization camera capable of detecting the partial linear polarization of light reflected from an object. The use of twisted nematic (TN) liquid crystals that electro-optically modulate the polarization plane of light eliminates the need to mechanically rotate the polarizing filter in front of the camera lens. Images obtained using these techniques are imaged by computer software. In addition, liquid crystal panels have been produced in a square shape, but many camera lenses are usually round, and lighting or other driving units are installed around the lens, so space is optimized through the application of a circular liquid crystal display. Through the development of this technology, an electrically switchable and space-optimized liquid crystal polarizer is developed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.73-79
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• 2022

The Python language widely used in artificial intelligence (AI) projects is an interpreter language, and errors occur at runtime. In order to prevent project failure due to errors, it is necessary to handle exceptions in code that can cause exceptional situations in advance. In particular, in AI projects that require a lot of resources, exceptions that occur after long execution lead to a large waste of resources. However, since exception handling depends on the developer's experience, developers have difficulty determining the appropriate exception to catch. To solve this need, we propose an approach that recommends exceptions to catch to developers during development by learning the existing exception handling statements. The proposed method receives the source code of the try block as input and recommends exceptions to be handled in the except block. We evaluate our approach for a large project consisting of two frameworks. According to our evaluation results, the average AUPRC is 0.92 or higher when performing exception recommendation. The study results show that the proposed method can support the developer's exception handling with exception recommendation performance that outperforms the comparative models.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.11
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• pp.473-478
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• 2022

Evaluation learning based on code testing is becoming a popular solution in programming education via Online judge(OJ). In the recent past, many papers have been published on how to detect plagiarism through source code similarity analysis to support OJ. However, deep learning-based research to support automated tutoring is insufficient. In this paper, we propose Input & Output side FiLM models to predict whether the input code will pass or fail. By applying Feature-wise Linear Modulation(FiLM) technique to GRU, our model can learn combined information of Java byte codes and problem information that it tries to solve. On experimental design, a balanced sampling technique was applied to evenly distribute the data due to the occurrence of asymmetry in data collected by OJ. Among the proposed models, the Input Side FiLM model showed the highest performance of 73.63%. Based on result, it has been shown that students can check whether their codes will pass or fail before receiving the OJ evaluation which could provide basic feedback for improvements.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.12
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• pp.857-866
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• 2022

Fixed-wing UAVs have long endurance and range capabilities compared to other aerial platforms. These advantages led fixed-wing UAVs to become a popular platform for reconnaissance missions in the military. In this research, we modeled fixed-wing UAVs, including the landing gear model and developed a guidance and control system for flight control computers to construct a HILS environment. We also developed an autopilot system that includes automated take-off, cruise, and landing control for UAVs. We also retrived the Aerodynamic coefficients an UAV using Datcom and AVL software and used them for 6 degrees of freedom modeling. The Flight control computer calculates guidance commands using the Carrot chasing guidance law after distinguishing the condition of the UAV based on 16 pre-defined flight modes and calculates control inputs using Nonlinear Dynamic Inversion (NDI) control scheme. We used RTNngine to integrate the Simulink model and flight control computer for HILS environment formulation.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.77-95
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• 2023

In this study, the conceptual design of a tilt + stopped rotor type electric vertical take-off and landing (eVTOL) aircraft was performed using design iteration. Based on Hyundai Motor's S-A1, the mission profile was defined using the concept of urban air mobility (UAM), and configuration design and aerodynamic analysis were performed using OpenVSP and XFLR5 software. After estimating the required power for the designed eVTOL, the required performance of the battery and the maximum take-off weight (MTOW) were calculated. . It was iteratively calculated using Microsoft Excel and Visual Basic Application, and a new electric motor weight estimation formula was derived. Also, the sensitivity analyses of each design variables of an eVTOL was performed using the automated program.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.369-375
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• 2004

Gas turbine engine simulation in terms of transient, steady state performance and operational characteristics is complex work at the various engineering functions of aero engine manufacturers. Especially, efficiency of control system design and development in terms of cost, development period and technical relevance implies controlling diverse simulation and identification activities. The previous engine simulation has been accomplished within a limited analysis area such as fan, compressor, combustor, turbine, controller, etc. and this has resulted in improper engine performance and control characteristics because of limited interaction between analysis areas. In this paper, we propose a new simulation methodology for gas turbine engine performance analysis as well as its digital controller to solve difficulties as mentioned above. The novel method has particularities of (ⅰ) resulting in the integrated control simulation using almost every component/module analysis, (ⅱ) providing automated math model generation process of engine itself, various engine subsystems and control compensators/regulators, (ⅲ) presenting total sophisticated output results and easy understandable graphic display for a final user. We call this simulation system GT3GS (Gas Turbine 3D Graphic Simulator). GT3GS was built on both software and hardware technology for total simulation capable of high calculation flexibility as well as interface with real engine controller. All components in the simulator were implemented using COTS (Commercial Off the Shelf) modules. In addition, described here includes GT3GS main features and future works for better gas turbine engine simulation.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.113-120
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• 2023

Smart farms are steadily increasing in research to minimize labor, energy, and quantity put into crops as IoT technology and artificial intelligence technology are combined. However, research on efficiently managing crop growth information in smart farms has been insufficient to date. In this paper, we propose a management technique that can efficiently monitor crop growth information by applying autonomous sensors to smart farms. The proposed technique focuses on collecting crop growth information through autonomous sensors and then recycling the growth information to crop cultivation. In particular, the proposed technique allocates crop growth information to one slot and then weights each crop to perform load balancing, minimizing interference between crop growth information. In addition, when processing crop growth information in four stages (sensing detection stage, sensing transmission stage, application processing stage, data management stage, etc.), the proposed technique computerizes important crop management points in real time, so an immediate warning system works outside of the management criteria. As a result of the performance evaluation, the accuracy of the autonomous sensor was improved by 22.9% on average compared to the existing technique, and the efficiency was improved by 16.4% on average compared to the existing technique.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.171-178
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• 2023

In this paper, we propose a smart automated warehouse to maximize space utilization. Previous elevator-type automatic warehouses were designed with a maximum payload of 100kg on trays, which has the problem of extremely limiting the number of pallets that can be loaded within the space. In this paper, we design a smart warehouse that can maximize space utilization with a maximum vertical stiffness of 300kg. As a result of the performance evaluation of the implemented warehouse, the maximum payload was 500.6kg, which satisfied the original design and requirements, the lifting speed was 0.5m/s, the operating noise of the device was 67.1dB, the receiving and forwarding time of the pallet was 36.92sec, the deflection amount was 4mm, and excellent performance was confirmed in all evaluation items. In addition, the PLC control method, which designs the control UI and control panel separately, was integrated into the PC system to improve interoperability and maintainability with various process management systems. In the future, we plan to develop it into a fully automatic smart warehouse by linking IoT sensor-based logistics robots.