• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.1-10
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• 2021

The interest in underwater acoustic sensor networks (UWASNs), along with the rapid development of underwater industries, has increased. To operate UWASNs efficiently, it is important to adopt well-designed medium access control (MAC) protocols that prevent collisions and allow the sharing of resources between nodes efficiently. On the other hand, underwater channels suffer from a narrow bandwidth, long propagation delay, and low data rate, so existing terrestrial node pairing schemes for non orthogonal multiple access (NOMA) cannot be applied directly to underwater environments. Therefore, a multi-dimensional node pairing scheme is proposed to consider the unique underwater channel in UWASNs. Conventional NOMA schemes have considered the channel quality only in node pairing. Unlike previous schemes, the proposed scheme considers the channel gain and many other features, such as node fairness, traffic load, and the age of data packets to find the best node-pair. In addition, the sender employs a list of candidates for node-pairs rather than path loss to reduce the computational complexity. The simulation results showed that the proposed scheme outperforms the conventional scheme by considering the fairness factor with 23.8% increases in throughput, 28% decreases in latency, and 5.7% improvements in fairness at best.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.203-209
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• 2021

With the recent development of satellite sensor technology, high-spatial-resolution imagery of various spectral wavelength bands have become possible. Worldview-3 satellite sensor provides panchromatic images with high-spatial-resolution and VNIR (Visible Near InfraRed) and SWIR (ShortWave InfraRed) bands with low-spatial-resolution, so it can be used in various fields such as defense, environment, and surveying. In this study, mineral detection was performed using Worldview-3 satellite imagery. In order to effectively utilize the VNIR and SWIR bands of the Worldview-3 satellite image, the sharpening technique was applied to the spatial resolution of the panchromatic image. To confirm the utility of SWIR bands for mineral detection, mineral detection using only VNIR bands was performed and comparatively evaluated. As the mineral detection technique, SAM (Spectral Angle Mapper), a representative similarity technique, was applied, and the pixels detected as minerals were selected by applying an empirical threshold to the analysis result. Quantitative evaluation was performed using reference data on the results of similarity analysis to evaluate the accuracy of mineral detection. As a result of the accuracy evaluation, the detection rate and false detection rate of mineral detecting using SWIR bands were calculated to be 0.882 and 0.011, respectively, and the results using only VNIR bands were 0.891 and 0.037, respectively. It was found that the detection rate when the SWIR bands were additionally used was lower than that when only the VNIR bands were used. However, it was found that the false detection rate was significantly reduced, and through this, it was possible to confirm the applicability of SWIR bands in mineral detection.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.27-35
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• 2021

With the development of the Internet, various IT technologies such as IoT, Cloud, etc. have been developed, and various systems have been built in countries and companies. Because these systems generate and share vast amounts of data, they needed a variety of systems that could detect threats to protect the critical data contained in the system, which has been actively studied to date. Typical techniques include anomaly detection and misuse detection, and these techniques detect threats that are known or exhibit behavior different from normal. However, as IT technology advances, so do technologies that threaten systems, and these methods of detection. Advanced Persistent Threat (APT) attacks national or companies systems to steal important information and perform attacks such as system down. These threats apply previously unknown malware and attack technologies. Therefore, in this paper, we propose a hybrid intrusion detection system that combines anomaly detection and misuse detection to detect unknown threats. Two detection techniques have been applied to enable the detection of known and unknown threats, and by applying machine learning, more accurate threat detection is possible. In misuse detection, we applied Classification based on Association Rule(CBA) to generate rules for known threats, and in anomaly detection, we used One-Class SVM(OCSVM) to detect unknown threats. Experiments show that unknown threat detection accuracy is about 94%, and we confirm that unknown threats can be detected.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.76-84
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• 2021

The quality assurance activities can detect the factors that affect the quality based on risk identification in the course of mass production. Risk identification is conducted with risk analysis, and the risk analysis method for the rotorcraft landing system is selected by failure mode effects analysis (FMEA). FMEA is a method that detects the factors that can affect the product quality by combining severity, occurrence, and detectability. The results of FMEA were prioritized using the risk priority number. On the other hand, these methods have certain shortcomings because the severity, occurrence, detectability are weighted equally. Dempster-Shafer evidence theory can conduct uncertainty analysis for the opinions with personal reflections and subjectivity. Based on the theory, the belief function and the plausibility function can be formed. Moreover, the functions can be utilized to evaluate the belief rate and credibility. The system is exposed to impact during take-off and landing. Therefore, experts should manage failure modes in the course of mass production. In this paper, FMEA based on the Dempster-Shafer evidence theory is discussed to perform risk analysis regarding the failure mode of the rotorcraft landing system. The failure priority was evaluated depending on the factor values. The results were derived using belief and plausibility function graphs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.33-39
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• 2021

As the interest and demand in the recycled yarn field has increased rapidly worldwide, domestic companies are also promoting research and development and business on recycled yarn. The chemical and thermal properties of four types of virgin and recycled PET samples from A and B company, which are the leading domestic companies in the recycled polyester yarn business, were confirmed through infrared (FT-IR) spectroscopy and differential scanning calorimetry (DSC). Virgin and recycled PET from two companies were compared. FT-IR spectroscopy revealed the typical spectra of PET for both companies and a different peak at 872 cm-1. DSC confirmed that the melting point and crystallization temperature of recycled PET were lower than those of virgin PET. These results indicate that small amounts of contaminants are an important parameter affecting the thermal properties of recycled PET. In the DSC results after seven repeats of the heating and cooling processes, all four samples showed that a lower melting point, crystallization temperature, and low heat flow intensity increased with increasing number of cycles. The results of melting and crystallization enthalpy also showed similar patterns.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.3
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• pp.91-98
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• 2021

Today's information and communication technology is rapidly developing, the security of IT infrastructure is becoming more important, and at the same time, cyber attacks of various forms are becoming more advanced and sophisticated like intelligent persistent attacks (Advanced Persistent Threat). Early defense or prediction of increasingly sophisticated cyber attacks is extremely important, and in many cases, the analysis of network-based intrusion detection systems (NIDS) related data alone cannot prevent rapidly changing cyber attacks. Therefore, we are currently using data generated by intrusion detection systems to protect against cyber attacks described above through Host-based Intrusion Detection System (HIDS) data analysis. In this paper, we conducted a comparative study on machine learning algorithms using LID-DS (Leipzig Intrusion Detection-Data Set) host-based intrusion detection data including thread information, metadata, and buffer data missing from previously used data sets. The algorithms used were Decision Tree, Naive Bayes, MLP (Multi-Layer Perceptron), Logistic Regression, LSTM (Long Short-Term Memory model), and RNN (Recurrent Neural Network). Accuracy, accuracy, recall, F1-Score indicators and error rates were measured for evaluation. As a result, the LSTM algorithm had the highest accuracy.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.51-58
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• 2021

In this paper, a multi-scale finite element (FE) modeling methodology for three-dimensional (3D) needle-punched (NP) C/SiC with a complex microstructure is presented. The variations of the material properties induced by the needle-punching process and complex geometrical features could pose challenges when estimating the material behavior. For considering these features of composites, a 3D microscopic FE approach is introduced based on micro-CT technology to produce a 3D high fidelity FE model. The image processing techniques of micro-CT are utilized to generate discrete-gray images and reconstruct the high fidelity model. Furthermore, a subcell modeling technique is developed for the 3D NP C/SiC based on the high fidelity FE model to expand to the macro-scale structural problem. A numerical homogenization approach under periodic boundary conditions (PBCs) is employed to estimate the equivalent behavior of the high fidelity model and effective properties of subcell components, considering geometry continuity effects. For verification, proposed models compare excellently with experimental results for the mechanical behavior of tensile, shear, and bending under static loading conditions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.429-438
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• 2021

Owing to the development of science technology, particularly the smart concept and defense policy factors of the 4th industry, military weapon systems are advanced, and the scientific and operational force is reduced dramatically. The aspect of the future war is characterized by the operation of troops with reduced forces from advanced and scientific weapon systems in an operational area that has expanded more than four times compared to the present. Reflecting on these situational factors, it is necessary to improve combat methods based on the changes in the battlefield environment and advanced weapon systems. In this study, to find a more efficient future combat method in a changing war pattern, this study applied the battle experiment methodology using Vision21 war game model, which is an analytical model used by the army. Finally, this study aimed to verify the future combat method and unit structure. Therefore, the scenario composition and experiment method that reflect the change in the ground operational environment and weapon system was first composed. Subsequently, an analysis method based on the combat effectiveness was applied to verify the effective combat performance method and unit structure of future infantry units.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.77-86
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• 2022

The Republic of Korea is a country in which coastal surveillance is an imperative national task as it is surrounded by seas on three sides under the confrontation between South and North Korea. However, due to Defense Reform 2.0, the number of R/D (Radar) operating personnel has decreased, and the period of service has also been shortened. Moreover, there is always a possibility that a human error will occur. This paper presents specific guidelines for developing an AI learning model for the intelligent coastal surveillance system. We present a three-step strategy to realize the guidelines. The first stage is a typical stage of building an AI learning model, including data collection, storage, filtering, purification, and data transformation. In the second stage, R/D signal analysis is first performed. Subsequently, AI learning model development for classifying real and false images, coastal area analysis, and vulnerable area/time analysis are performed. In the final stage, validation, visualization, and demonstration of the AI learning model are performed. Through this research, the first achievement of making the existing weapon system intelligent by applying the application of AI technology was achieved.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.99-104
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• 2022

Recently, the domestic demand for weapon systems based on aircraft platforms is gradually increasing. In particular, the demand for effective precision guided missile(PGM) which cruises for several hundred kilometers after launch to strike the ground target is rising drastically, but it is in the early stages of development, and research based on it are limited. This paper is a study on the power converter unit(PCU) within PGM which is mounted on an aircraft platform based on MIL-STD-1760, which is an interface between an aircraft and PGM. We investigated the electrical properties and structure of the umbilical connector, and the aircraft/store electrical interconnection system. Also, the focus on the design specifications of the PCU that supplies power were described. This result 3 phase AC input, which is the state for the guided simulation power supply in the state of being mounted on an aircraft that rectification method with power factor correction(PFC) compared to bridge rectifier circuit. In the future, it may be used as a basis for power supply design on aircraft mounted weapon systems.