• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.47-55
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• 2022

Recently, researches on the prediction of sea water temperature using artificial intelligence models has been actively conducted in Korea. However, most researches in the sea around the Korean peninsula mainly focus on predicting sea surface temperatures. Unlike previous researches, this research predicted the vertical sea water temperature profile of the East Sea, which is very important in submarine operations and anti-submarine warfare, using XBT(eXpendable Bathythermograph) data and machine learning models(RandomForest, XGBoost, LightGBM). The model was trained using XBT data measured from sea surface to depth of 200m in a specific area of the East Sea, and the prediction accuracy was evaluated through MAE(Mean Absolute Error) and vertical sea water temperature profile graphs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.4
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• pp.721-728
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• 2013

Big data is one of the most spotlighted technological trends in these days, enabling new methods to handle huge volume of complicated data for a broad range of applications. Real-time network traffic analysis essentially deals with big data, which is comprised of different types of log data from various sensors. To tackle this problem, in this paper, we devise a big data based platform, RENTAP, to detect and analyse malicious network traffic. Focused on military network environment such as closed network for C4I systems, leading big data based solutions are evaluated to verify which combination of the solutions is the best design for network traffic analysis platform. Based on the selected solutions, we provide detailed functional design of the suggested platform.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.903-909
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• 2010

ADAS is the air defense control system performing air surveillance and identification of ROK and near air. This system is self-developed by Air Force, currently operated successfully as the alternative system of MCRC. ADAS processes converting and combining transferred the real time radar data detected by radars. additionally, it displays significant radar data as producing in tracks. Then, it uses the message queue for IPC(Inter Process Communication). the various tactical data processed in the server is ultimately send to the network management process through the message queue for transmitting to the weapon director console. the weapon director receives this transmitted tactical data through the console to execute air defense operations. However, there is a problem that data packet is delayed or lost since the weapon Director does not receive as the amount of tactical data from the server overflowed with air tracks and missions increased. This paper improved the algorism to display and transmit the various tactical data processed from ADAS server to numbers of the weapon director console in the real time without any delay or lost. Improved the algorism, established at exercise, the development server in the real operation network and the weapon director console, is proved by comparing the number of sending tactical data packets in the server and receiving packets in the weapon director.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.3
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• pp.370-378
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• 2018

The mission data in missile systems should be quickly and reliably transmitted from a mission transmission device to a guidance control unit. The MIL-STD-1553B is one of the reliable communication standards, but its bit rate is generally limited to 1Mbps due to the intrinsic properties of its electrical design. Therefore, the bus controller needs to be optimized to efficiently transmit the mission data on the inevitably limited bit rate. This paper proposes an analytical approach based on sampling-based optimization methods to maximize the data throughput without data loss. The proposed approach was evaluated in the simulations with the data transmission model for the MIL-STD-1553B communication system. The results of the proposed methods were applied to a real-time system and showed that the proposed method was successfully performed.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.2
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• pp.187-196
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• 2021

The Network-Centric warfare over weapon data link networks has been developed for the recent decade. Since the US navy had begun to develop tactical digital information chain, it has gradually transformed into weapon data link technology. As data link network system and its protocol have been advanced into high-technology, focusing and targeting on moving targets become possible in net-enabled environments. However, it is difficult to identify the primary information from numerous battlefields and understanding approaches to damage a target in a timely manner. In this paper, to better understand the targeting assessment, we suggest a specific solution: Bomb Hit Indication(BHI) using information in weapon data link messages. In order to prove our suggestion, we implement the BHI solution and apply it into the weapon data link integrating system.

• Proceedings of the CALSEC Conference
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• 1999.11a
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• pp.75-84
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• 1999

CALS is a strategy to share integrated product data through a set of standards to achieve efficiencies in business and operational mission areas. In this research, we first studied current status for CALS standard and then analyzed the case of US DoD. The results can be summarized as implementing for two major standard in defense CALS system. They are STEP and XML. Our recommendations can be used to set direction for CALS standard implementation and standard selection process.

• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.3
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• pp.14-20
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• 2018

An estimation law of air mass flow rate for high speed engine control is presented. The variables of mass estimation equations are modified to measurable variables which can be obtained during flight, and the effectiveness of each variable to the estimation accuracy is evaluated. The equation is modified to a simplified form, and the uncertainty is evaluated. In addition, reference data for the selection of estimation methods is suggested by considering the sensitivity analysis of sensor error.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.4
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• pp.436-447
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• 2014

The major elements of avionics system architecture are requirements, Real Time Operating System, message communication, memory, and data format etc. Herein describes a state-of-the-art development trend for the avionics system architecture, system requirements and data bus among the major elements of avionics system. While, domestic technology has been tried to Integrated Modular Avionics(IMA) system based on the Avionics Full Duplex Switched Ethernet(AFDX) technology during Light Attack Helicopter(LAH) project in Korea, but not yet proved as the product case in Full Scale Development Phase. The avionics system architecture considering the domestic inexperience of the IMA system architecture are suggested for the Next-generation Corps Unmanned Aircraft System.

• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.125-133
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• 2019

Because military weapons systems for special purposes are small and complex, they are not easy to maintain. Therefore, it is very important to maintain combat strength through quick maintenance in the event of a breakdown. In particular, naval ships are complex weapon systems equipped with various equipment, so other equipment must be considered for maintenance in the event of equipment failure, so that skilled maintenance personnel have a great influence on rapid maintenance. Therefore, in this paper, we analyzed maintenance data of defense equipment maintenance information system through text mining and social network analysis(SNA), and tried to identify the naval ship maintenance expertise. The defense equipment maintenance information system is a system that manages military equipment efficiently. In this study, the data(2,538cases) of some naval ship maintenance teams were analyzed. In detail, we examined the contents of main maintenance and maintenance personnel through text mining(word cloud, word network). Next, social network analysis(collaboration analysis, centrality analysis) was used to confirm the collaboration relationship between maintenance personnel and maintenance expertise. Finally, we compare the results of text mining and social network analysis(SNA) to find out appropriate methods for finding and finding naval ship maintenance expertise.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5765-5781
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• 2018

Extreme learning machine (ELM) is emerging as a powerful machine learning method in a variety of application scenarios due to its promising advantages of high accuracy, fast learning speed and easy of implementation. However, how to select the optimal hidden layer of ELM is still an open question in the ELM community. Basically, the number of hidden layer nodes is a sensitive hyperparameter that significantly affects the performance of ELM. To address this challenging problem, we propose to adopt multiple kernel learning (MKL) to design a multi-hidden-layer-kernel ELM (MHLK-ELM). Specifically, we first integrate kernel functions with random feature mapping of ELM to design a hidden-layer-kernel ELM (HLK-ELM), which serves as the base of MHLK-ELM. Then, we utilize the MKL method to propose two versions of MHLK-ELMs, called sparse and non-sparse MHLK-ELMs. Both two types of MHLK-ELMs can effectively find out the optimal linear combination of multiple HLK-ELMs for different classification and regression problems. Experimental results on seven data sets, among which three data sets are relevant to classification and four ones are relevant to regression, demonstrate that the proposed MHLK-ELM achieves superior performance compared with conventional ELM and basic HLK-ELM.