• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.58-71
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• 2019

This paper proposes architecture of a cognitive radio engine platform and the allowable frequency channel reasoning method that enables acquisition of the allowable channels for the military tactical network environment. The current military tactical wireless communication system is increasing need to secure a supplementary radio frequency to ensure that multiple wireless networks for different military wireless devices coexist, so that tactical wireless communication between the same or different systems can be operated effectively. This paper presents the allowable frequency channel reasoning method based on cognitive radio engine for realizing DSA(Dynamic Spectrum Access) as an optimal available frequency channel. To this end, a case-based allowable frequency channel reasoning method for cognitive radio devices is proposed through modeling of primary user's traffic status and calculation of channel occupancy probability. Also through the simulation of the performance analysis, changing rate of collision probability between the primary users' occupancy channel and the available channel acquisition information that can be used by the cognitive radio device was analysed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.11
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• pp.944-951
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• 2018

Artificial icing test and wind tunnel test can be performed to reduce the development period when a rotorcraft is required operation under icing situations. Artificial icing test of the KUH(Korean Utility Helicopter) was performed in advance to verify anti-icing and de-icing performance before natural icing test. Although high-precision sensor, the CCP(Cloud Combination Probe) is used to measure icing test condition parameters such as LWC(Liquid Water Content) and MVD(Median Volume Diameter), the measured values need to be verified in various methods due to the possibility of uncertainties which are the test atmosphere environment, sensor errors, and etc. The calculated LWC from the ice thickness cumulated on the fuselage of the KUH is compared to the measured value by CCP, and the results show the effective indirect method to check the test conditions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.1-6
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• 2018

This study examined the quality improvement of printed circuit boards (PCBs) in relation to the power consumption for radar. The radar examined is currently in production and being used by the military. The PCB converts 28 V DC to 5 V DC but frequently malfunctions. Therefore, cause analysis was carried out. As a result, the power consumed by a certain communication IC was very high, and the heat generated by the high power consumption caused damage to the surrounding parts. Accordingly, it was changed to an improved communication IC that meets all the radar system specifications. System tests were carried out for the changed communication IC to check the impact on the system, and environmental tests were performed, which proved that the performance required by the radar system is satisfactory. As a result of this improvement, there has been no history of failure in this PCB so far. Therefore, the quality of this PCB has been improved.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.63-73
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• 2021

This paper presents a algorithm for automatic target recognition robust to the influence of the flame in order to track the target by EOTS(Electro-Optical Targeting System) equipped on UAV(Unmanned Aerial Vehicle) when there is aerial target or marine target with flame at the same time. The proposed method converts infrared images of targets and flames into a gradient vector field, and applies each gradient magnitude to a polynomial curve fitting technique to extract polynomial coefficients, and learns them in a shallow neural network model to automatically recognize targets and flames. The performance of the proposed technique was confirmed by utilizing the various infrared image database of the target and flame. Using this algorithm, it can be applied to areas where collision avoidance, forest fire detection, automatic detection and recognition of targets in the air and sea during automatic flight of unmanned aircraft.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.311-318
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• 2021

Underwater, signals are transmitted by sound waves. Sound waves are transmitted through a multipath, either directly or through reflection, due to the variety of underwater environmental characteristics. In such diverse and complex underwater environments, tests must be conducted to determine the extent of the hazard from the survivability and pitfalls of submarines by measuring the underwater radiated noise. Usually, the sound source level measurement of underwater radiated noise should be made within the closest point (CPA: Closest Point of Approach) ± a few meters between the measurement sensor and the submarine. In this study, FDOA and TDOA methods were proposed to estimate the underwater source range. A simulation based on the underwater channel model confirmed the performance of the proposed method.

• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.12-19
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• 2021

For strengthening the national defense, the function of tactical network is essential. tactics and strategies in wartime situations are based on numerous information. Therefore, various reconnaissance devices and resources are used to collect a huge amount of information, and they transmit the information through tactical networks. In tactical networks that which use contention based channel access scheme, high-speed nodes such as recon aircraft may have performance degradation problems due to unnecessary channel occupation. In this paper, we propose a learning-backoff method, which empirically learns the size of the contention window to determine channel access time. The proposed method shows that the network throughput can be increased up to 25% as the number of high-speed mobility nodes are increases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1254-1260
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• 2019

Recently, 5G cellular systems have been attracted great attention as a key enabler for Industry 4.0. In this paper, we propose a novel random access based on pilot-assisted opportunistic transmission to support internet-of-things (IoT) scenario in cellular networks. A key feature of our proposed scheme is to enable each of IoT devices to attempt opportunistic transmission of its data packet in Step 3 with randomly selected uplink pilot signal. Both the opportunistic transmission and the pilot randomization in Step 3 are effective to significantly mitigate the occurrence of packet collisions. We mathematically analyze our proposed scheme in terms of packet collision probability and uplink resource efficiency. Through simulations, we verify the validity of our analysis and evaluate the performance of our proposed scheme. Numerical results show that our proposed scheme outperforms other competitive schemes.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.1-10
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• 2022

Deception technology is an extended concept of honeypot, which detects, prevents or delays attacks by deceiving adversaries. It has been applied to various system components such as network ports, services, processes, system calls and database management systems. We can apply the same concept to attacks on files. A representative example of a file attack is ransomware. Ransomware is a type of malware that encrypts user files and ask for ransom to recover those files. Another example is the wiper attack, which erases all or target files of a system. In this paper we propose a defense mechanism against these kinds of attacks by hiding files. Compared to backup or virtualization techniques, the proposed method incurs less space and performance overheads.

• Journal of the Korean Society of Radiology
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• v.16 no.5
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• pp.527-536
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• 2022

The radiation shielding characteristic of neutron shielding material has been studied as the preliminary study in order to design cosmic-ray shielding material. Specially, Soft Magnetic Material, known to be effective in EMP and radiation shielding, has been investigated to check if the material would be applicable to cosmic-ray shielding. In this work, thermal neutron shielding experiment was conducted and the Monte Carlo N-Particle(MCNP) was applied to employ skymap.dat, which is cosmic-ray data embedded in MCNP. As a result, polyethylene, borated polyethylene, and carbon nano tube, containing carbon or hydrogen, have been found to be effective in reduction of neutron flux below 20 MeV (including thermal, epithermal, evaporation). In contrast, the materials composed of iron such as SS316 and Soft Magnetic Material show a good shielding performance in the cascade energy range (above 20 MeV). Since Soft Magnetic Material is consisting of 13% of boron, it can also decrease thermal neutron flux, so it is expected that it would show a significant reduction on the entire range of neutron energy if the Soft Magnetic Material is used with hydrogen and carbon, so called low Z material.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.1
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• pp.10-21
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• 2023

For various target tracking applications, it is well known that the Kalman filter is the optimal estimator(in the minimum mean-square sense) to predict and estimate the state(position and/or velocity) of linear dynamical systems driven by Gaussian stochastic noise. In the case of nonlinear systems, Extended Kalman filter(EKF) and/or Unscented Kalman filter(UKF) are widely used, which can be viewed as approximations of the(linear) Kalman filter in the sense of the conditional expectation. However, to implement EKF and UKF, the exact dynamical model information and the statistical information of noise are still required. In this paper, we propose the recurrent neural-network based Kalman filter, where its Kalman gain is obtained via the proposed GRU-LSTM based neural-network framework that does not need the precise model information as well as the noise covariance information. By the proposed neural-network based Kalman filter, the state estimation performance is enhanced in terms of the tracking error, which is verified through various linear and nonlinear tracking problems with incomplete model and statistical covariance information.