• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.99-110
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• 2023

This study proposed a classification of malicious network traffic using the cyber threat framework(Mitre ATT&CK) and machine learning to solve the real-time traffic detection problems faced by current security monitoring systems. We applied a network traffic dataset called UNSW-NB15 to the Mitre ATT&CK framework to transform the label and generate the final dataset through rare class processing. After learning several boosting-based ensemble models using the generated final dataset, we demonstrated how these ensemble models classify network traffic using various performance metrics. Based on the F-1 score, we showed that XGBoost with no rare class processing is the best in the multi-class traffic environment. We recognized that machine learning ensemble models through Mitre ATT&CK label conversion and oversampling processing have differences over existing studies, but have limitations due to (1) the inability to match perfectly when converting between existing datasets and Mitre ATT&CK labels and (2) the presence of excessive sparse classes. Nevertheless, Catboost with B-SMOTE achieved the classification accuracy of 0.9526, which is expected to be able to automatically detect normal/abnormal network traffic.

• Korean Journal of Clinical Laboratory Science
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• v.54 no.4
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• pp.293-297
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• 2022

In 2022, Korea reported a total of 224 perfusionists, employing nurses or clinical laboratory technologists (also known as medical technologists) to provide hospital self-education or reliable education. In 2021, the total number of perfusionists in Japan was 2,100, mainly supported by clinical engineering technologists. During the same period, the number of perfusionists reported in the United States was 4,212, who had received training in the master's program, post-bachelor certificate program, and bachelor's program. Most personnel in the USA were graduates of healthcare sciences or life sciences. Perfusionists must be knowledgeable in heart anatomy, physiology, pharmacology, pathology, hemodynamics, laboratory analysis, and quality assurance, as well as techniques to operate the cardiopulmonary bypass machine (heart-lung bypass machine). These are jobs similarly handled by clinical laboratory technologists. The importance of perfusionists became more prominent during two major crises: the MERS-CoV and COVID-19 pandemic. Currently, perfusionists play a significant role in the rapidly expanding field of extracorporeal membrane oxygenation (ECMO) and extracorporeal circulation during cardiac surgery. Results of the current study indicate that hospitals offering cardiac surgery and infectious disease hospitalization need to be institutionalized to secure a certain number of qualified perfusionists. In the future, we look forward to establishing a perfusion technology association under the Korean Society for Clinical Laboratory Physiology to provide academic exchanges.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.33-39
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• 2023

As the number of people with chronic diseases increases due to an aging society, it is urgent to prevent and manage their diseases. Although biometric authentication methods and Telemedicine Systems have been introduced to solve these problems, it is difficult to solve the security problem of medical information and personal authentication. Since smart healthcare includes personal medical information of subjects, the security of personal information is the most important field. Therefore, in this paper, we tried to propose a Telemedicine System using a smart wearable device ECG in the form of a wristband and face personal authentication in a private blockchain environment. This system targets various medical personnel and patients with chronic diseases in all regions, and uses a private blockchain that can increase data integrity and transparency, ECG and face authentication that are difficult to forge and alter and have high personal identification to provide a system with high security and reliability. composed. Through this, it is intended to contribute to increasing the efficiency of chronic disease management by focusing on disease prevention and health management for patients with chronic diseases at home.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.19-36
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• 2023

As advances in information and communication technology have made it easier for anyone to produce and disseminate information, a new problem has emerged: fake news, which is false information intentionally shared to mislead people. Initially spread mainly through text, fake news has gradually evolved and is now distributed in multimedia formats. Since its founding in 2005, YouTube has become the world's leading video platform and is used by most people worldwide. However, it has also become a primary source of fake news, causing social problems. Various researchers have been working on detecting fake news on YouTube. There are content-based and background information-based approaches to fake news detection. Still, content-based approaches are dominant when looking at conventional fake news research and YouTube fake news detection research. This study proposes a fake news detection method based on background information rather than content-based fake news detection. In detail, we suggest detecting fake news by utilizing related video information from YouTube. Specifically, the method detects fake news through CNN, a deep learning network, from the vectorized information obtained from related videos and the original video using Doc2vec, an embedding technique. The empirical analysis shows that the proposed method has better prediction performance than the existing content-based approach to detecting fake news on YouTube. The proposed method in this study contributes to making our society safer and more reliable by preventing the spread of fake news on YouTube, which is highly contagious.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.57-64
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• 2023

The ROK military faces a significant challenge in its vigilance mission due to demographic problems, particularly the current aging population and population cliff. This study demonstrates the crucial role of the 4th industrial revolution and its core artificial intelligence algorithm in maximizing work efficiency within the Command&Control room by mechanizing simple tasks. To achieve a fully developed military surveillance system, we have chosen multi-object tracking (MOT) technology as an essential artificial intelligence component, aligning with our goal of an intelligent and automated surveillance system. Additionally, we have prioritized data visualization and user interface to ensure system accessibility and efficiency. These complementary elements come together to form a cohesive software application. The CCTV video data for this study was collected from the CCTV cameras installed at the 1st and 2nd main gates of the 00 unit, with the cooperation by Command&Control room. Experimental results indicate that an intelligent and automated surveillance system enables the delivery of more information to the operators in the room. However, it is important to acknowledge the limitations of the developed software system in this study. By highlighting these limitations, we can present the future direction for the development of military surveillance systems.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.667-674
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• 2023

In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.50-53
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• 2022

Recently, there have been cases in which counterfeit foreign ships have entered and left domestic ports several times. Vessels have a ship-specific serial number given by the International Maritime Organization (IMO) to identify the vessel, and IMO marking is mandatory on all ships built since 2004. In the case of airports and ports, which are representative logistics platforms, a security system is essential, but it is difficult to establish a security system at a port and there are many blind spots, which can cause security problems due to insufficient security systems. In this paper, a port security system is designed using deep learning object recognition and OpenCV. The security system process extracts the IMO number of the ship after recognizing the object when entering the ship, determines whether it is the same ship through feature point matching for ships with entry records, and stores the ship image and IMO number in the entry/exit DB for the first arrival vessel. Through the system of this paper, port security can be strengthened by improving the efficiency and system of port logistics by increasing the efficiency of port management personnel and reducing incidental costs caused by unauthorized entry.

• Journal of Practical Agriculture & Fisheries Research
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• v.10 no.1
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• pp.67-75
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• 2008

Tartary buckwheat is one of specialized plants in Pyeongchang county, Korea and contains rutin much more than common buckwheat. Rutin is a kind of flavonoid (polyphenol compound) that has effects on blood vascular disease, strengthen capillary, and anti-inflammatory effect. This study was conducted to determine the possibility of development of beverage extracted from sugar-treated plants and sprouts of tartary buckwheat. By using two types of undiluted solution extracted from plant and sprouts of tartary buckwheat, we analyzed their nutrition components and did experiment on mice to find out pharmaceutical effects. In an experiment on mice, we administered various concentration of buckwheat to induced diabetic mellitus mice for 1 weeks. As a result, the buckwheat effected finely on lowering blood sugar and decreased LDL-cholesterol and total lipid level but increased HDL-cholesterol level.

• Journal of Navigation and Port Research
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• v.47 no.1
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• pp.37-48
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• 2023

Recently, the increase of international trade volume is leading to risk exposure and safety accidents in the port terminal industry. In addition, as Serious Disaster Punishment Act came into effect on January, 2021, various guidelines and laws to protect safety and life in port terminals are being enacted. However, despite these efforts, medium-to-large safety accidents in the port terminal industry have occurred. According to the Korea Occupational Safety and Health Agency, from 2016 to 2019, the number of casualties in the port handling industry increased by 4.2%. To build some effective follow-up management of port accidents and preparation of related safety laws/systems, a risk analysis in consideration of causes and damage of accidents should be conducted. Therefore, in this study, major risk factors and preventive measures were derived by conducting risk assessment based on 1,039 cases of port terminal accidents collected by the Korea Occupational Safety and Health Agency for five years. Priorities for preventive measures were then determined through IPA analysis, Borich needs analysis, and The Locus For Focus analysis.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.285-290
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• 2023

Compressors are widely used in high-speed electronic systems and are used to reduce the number of operands in multiplier. The proposed compressor is constructed based on the m-GDI(: modified gate diffusion input) to reduce the propagation delay time. This paper is compared the performance of compressors by applying 4-2, 5-2 and 6-2 m-GDI compressors to the multiplier, respectively. As a simulation results, compared to the 8-bit Dadda multiplier using the 4-2 and 6-2 compressor, the multiplier using the 5-2 compressor is reduced propagation delay time 13.99% and 16.26%, respectively. Also, the multiplier using the 5-2 compressor is reduced PDP(: Power Delay Product) 4.99%, 28.95% compared to 4-2 and 6-2 compressor, respectively. However, the multiplier using the 5-2 compression circuit is increased power consumption by 10.46% compared to the multiplier using the 4-2 compression circuit. In conclusion, the 8-bit Dadda multiplier using the 5-2 compressor is superior to the multipliers using the 4-2 and 6-2 compressors. The proposed circuit is implemented using TSMC 65nm CMOS process and its feasibility is verified through SPECTRE simulation.