• Korean Journal of Materials Research
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• v.31 no.12
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• pp.719-726
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• 2021

Through the process of chemical vapor deposition, Tungsten Hexafluoride (WF₆) is widely used by the semiconductor industry to form tungsten films. Tungsten Hexafluoride (WF₆) is produced through manufacturing processes such as pulverization, wet smelting, calcination and reduction of tungsten ores. The manufacturing process of Tungsten Hexafluoride (WF₆) is required thorough quality control to improve productivity. In this paper, a real-time detection system for oxidation defects that occur in the manufacturing process of Tungsten Hexafluoride (WF₆) is proposed. The proposed system is implemented by applying YOLOv5 based on Convolutional Neural Network (CNN); it is expected to enable more stable management than existing management, which relies on skilled workers. The implementation method of the proposed system and the results of performance comparison are presented to prove the feasibility of the method for improving the efficiency of the WF₆ manufacturing process in this paper. The proposed system applying YOLOv5s, which is the most suitable material in the actual production environment, demonstrates high accuracy (mAP@0.5 99.4 %) and real-time detection speed (FPS 46).

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.1
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• pp.23-29
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• 2022

As the application field of radar is expanded and the bandwidth increases, the number of radar sensors operating at the same frequency is continuously increasing. In this paper, we propose a method of analyzing interference when two pulse doppler radars are operated at the same frequency with different waveform which are designed independently. In addition, we show that even for a previously designed LFM waveforms, the interference can be suppressed without affecting the performance by changing the sign of the frequency slope by increasing/decreasing, or by modulating the pulses by the different codes. The interference suppression by different slopes is more effective for similar waveform and the suppression by the codes increases as the number of pulses increases. We expect this result can be extended to the cases where multiple radars are operated at the same frequency.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.6
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• pp.572-579
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• 2022

The analysis of foreign aircraft appearing suddenly in air defense identification zones requires a lot of cost and time. This study aims to develop a pre-trained model that can identify neighboring military aircraft based on aircraft photographs available on the web and present a model that can determine which aircraft corresponds to based on aerial photographs taken by allies. The advantages of this model are to reduce the cost and time required for model classification by proposing a pre-trained model and to improve the performance of the classifier by data augmentation of edge-detected images, cropping, flipping and so on.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1113-1120
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• 2021

Content Central Network (CCN) appeared to improve network efficiency by transforming IP-based network into content name-based network structures. Each router performs caching mechanism to improve network efficiency in the CCN. And the cache replacement policy applied to the CCN router is an important factor that determines the overall performance of the CCN. Therefore various studies has been done relating to cache replacement policy of the CCN. In this paper, we proposed a cache replacement policy that improves the limitations of the LFU policy. The proposal algorithm applies real-time producer popularity-based variables. And through experiments, we proved that the proposed policy shows a better cache hit ratio than existing policies.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.299-307
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• 2023

In the midst of accelerating wars around the world, unmanned robot technology that can guarantee the safety of human life is emerging. ERP-42 is a modular platform that can be used according to the application. In the field of defense, it can be used for transporting supplies, reconnaissance and surveillance, and medical evacuation in conflict areas. Due to the nature of the military environment, atypical environments are predominant, and in such environments, the platform's path followability is an important part of mission performance. This paper focuses on reducing the minimum turning radius in terms of improving path followability. The minimum turning radius of the existing 2WS/2WD in-wheel platform was reduced by increasing the torque of the independent driving in-wheel motor on the rear wheel to generate oversteer. To determine the degree of oversteer, two GPS were attached to the center of the front and rear wheelbases and measured. A closed-loop speed control method was used to maintain a constant rotational speed of each wheel despite changes in load or torque.

• Mycobiology
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• v.50 no.5
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• pp.269-293
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• 2022

Oomycete pathogens that belong to the genus Phytophthora cause devastating diseases in solanaceous crops such as pepper, potato, and tobacco, resulting in crop production losses worldwide. Although the application of fungicides efficiently controls these diseases, it has been shown to trigger negative side effects such as environmental pollution, phytotoxicity, and fungicide resistance in plant pathogens. Therefore, biological control of Phytophthora-induced diseases was proposed as an environmentally sound alternative to conventional chemical control. In this review, progress on biological control of the soilborne oomycete plant pathogens, Phytophthora capsici, Phytophthora infestans, and Phytophthora nicotianae, infecting pepper, potato, and tobacco is described. Bacterial (e.g., Acinetobacter, Bacillus, Chryseobacterium, Paenibacillus, Pseudomonas, and Streptomyces) and fungal (e.g., Trichoderma and arbuscular mycorrhizal fungi) agents, and yeasts (e.g., Aureobasidium, Curvibasidium, and Metschnikowia) have been reported as successful biocontrol agents of Phytophthora pathogens. These microorganisms antagonize Phytophthora spp. via antimicrobial compounds with inhibitory activities against mycelial growth, sporulation, and zoospore germination. They also trigger plant immunity-inducing systemic resistance via several pathways, resulting in enhanced defense responses in their hosts. Along with plant protection, some of the microorganisms promote plant growth, thereby enhancing their beneficial relations with host plants. Although the beneficial effects of the biocontrol microorganisms are acceptable, single applications of antagonistic microorganisms tend to lack consistent efficacy compared with chemical analogues. Therefore, strategies to improve the biocontrol performance of these prominent antagonists are also discussed in this review.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.1
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• pp.41-52
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• 2022

Development of a long-range artillery intercept system to counter the threat of enemy long-range artillery is in progress. This intercept system is a complex combination of several components. In addition, the ability to engage simultaneously is emphasized due to the characteristic of having to respond to numerous enemy bullets. In this study, the performance according to the arrangement of the detection asset and missile launchers, which are key components of the system, is analyzed. A simulation experiment was performed assuming the enemy attack at various azimuth and launch angles. As a result of the analysis, the radar seems to provide sufficient detection capability in any situation, but in the case of the launcher, the effect of the enemy's launch angle can be critical. It is recommended to place both radar and launchers behind the protection target.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1466-1488
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• 2022

Recently, the importance and necessity of artificial intelligence (AI), especially machine learning, has been emphasized. In fact, studies are actively underway to solve complex and challenging problems through the use of AI systems, such as intelligent CCTVs, intelligent AI security systems, and AI surgical robots. Information security that involves analysis and response to security vulnerabilities of software is no exception to this and is recognized as one of the fields wherein significant results are expected when AI is applied. This is because the frequency of malware incidents is gradually increasing, and the available security technologies are limited with regard to the use of software security experts or source code analysis tools. We conducted a study on MalDC, a technique that converts malware into images using machine learning, MalDC showed good performance and was able to analyze and classify different types of malware. MalDC applies a preprocessing step to minimize the noise generated in the image conversion process and employs an image augmentation technique to reinforce the insufficient dataset, thus improving the accuracy of the malware classification. To verify the feasibility of our method, we tested the malware classification technique used by MalDC on a dataset provided by Microsoft and malware data collected by the Korea Internet & Security Agency (KISA). Consequently, an accuracy of 97% was achieved.

• The Journal of the Acoustical Society of Korea
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• v.41 no.6
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• pp.637-646
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• 2022

Sub-arrays of arbitrary conformal array have different geometric shape through steering direction, thus the beam patterns of sub-arrays are always non-uniform. In this paper, we apply the beam pattern synthesis method using convex optimization into the conformal array, and shows the improvement of uniformity of beam performance. The simulation is performed with the conformal array of cut-sphere shape. As a result, the standard deviation of 3 dB beamwidth in elevation is greatly reduced but the directivity index is also reduced. To alleviate this trade-off, we propose a convex optimization using a shading function.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.249-257
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• 2022

COVID-19 struck without warning, and by the first quarter of 2020, the world had plunged into a state of total closure as a means of containing the pandemic's devastating effect. Certainly, the pandemic shook many economies; some countries were able to cope, while third-world countries lost their invulnerability. Based on this, the current study looked at financial reports from Kuwaiti conventional and Islamic banks from 2019 to 2020 (before and after the pandemic) and compared the findings to see how much of an impact Kuwaiti conventional and Islamic banks had during the COVID-19 epidemic. Financial analysis of financial reports was used as a quantitative methodology, and variables were compared and analyzed, including (the liquidity ratio, profitability ratio, and financial leverage) within (14) Kuwaiti conventional and Islamic banks. The study found that the pandemic had a detrimental impact on both conventional and Islamic banks in Kuwait, as they were the first line of defense for the Kuwaiti economy during lockdowns and quarantines. Furthermore, there were significant implications on the Rate of Return on Investment, Debt, Financial Leverage, and Return on Equity.