• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.839-846
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• 2022

Purpose: To secure the safety of firefighters who are dispatched to emergency activities for patients with suspected infectious diseases during an epidemic, and to identify the current status of suspected infectious disease patients by region based on the information collected at the site, and manage firefighting infectious diseases that can be controlled and supported I want to develop a system. Method: Develop a smartphone app that can classify suspected infectious disease patients to check whether an infectious disease is suspected, and develop a disposable NFC tag for patient identification to prevent infection from suspected infectious disease patients. Develop a management system that collects and analyzes data related to emergency patients with suspected infectious disease input from the field and provides them to relevant business personnel to evaluate whether the transport of emergency patients with suspected infectious disease is improved. Result: As a result of the experiment, it was possible to determine whether an infectious disease was suspected through the algorithm implemented in the smartphone app, and the retransfer rate was significantly reduced by transferring to an appropriate hospital. Conclusion: Through this study, the possibility of improving emergency medical services by applying ICT technology to emergency medical services was confirmed. It is expected that the safety of paramedics will be actively secured.

• 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 the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.97-106
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• 2022

In this study, H&E staining is necessary to distinguish cells. However, dyeing directly requires a lot of money and time. The purpose is to convert the phase image of unstained cells to the amplitude image of stained cells. Image data taken with FPM was created with Phase image and Amplitude image using Matlab's parameters. Through normalization, a visually identifiable image was obtained. Through normalization, a visually distinguishable image was obtained. Using the GAN algorithm, a Fake Amplitude image similar to the Real Amplitude image was created based on the Phase image, and cells were distinguished by objectification using MASK R-CNN with the Fake Amplitude image As a result of the study, D loss max is 3.3e-1, min is 6.8e-2, G loss max is 6.9e-2, min is 2.9e-2, A loss max is 5.8e-1, min is 1.2e-1, Mask R-CNN max is 1.9e0, and min is 3.2e-1.

• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.411-420
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• 2023

Purpose: In order to compensate for the limitations of the risk assessment of hydrogen charging stations, it is proposed to apply business disaster reduction activities as a way to strengthen safety and business continuity for accidents that may occur during operation. Method: We explored the application of business disaster reduction activities that can reduce, eliminate, transfer, and accept risks by classifying risks according to the passage of time in the installation and operation of hydrogen charging stations, identifying key tasks, deriving risk scenarios. Result: Existing research results are appropriately applied to the risk assessment conducted in the stage before the installation of hydrogen charging stations. However, there is a limit to the risks that can occur at the operational stage, so applying business disaster reduction activities with several example scenarios has resulted in that it can be applied as a way to strengthen safety and business continuity. Conclusion: All of the currently implemented risk assessments for hydrogen charging stations are being used appropriately. However, it proposes business disaster reduction activities that apply various risk scenarios as an evaluation and response to possible risks at the operational stage.

• Clean Technology
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• v.29 no.2
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• pp.135-144
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• 2023

Pseudomonas aeruginosa and Staphylococcus aureus are the two most frequently encountered pathogens responsible for chronic wound infections, often coexisting in such cases. These infections exhibit heightened virulence compared to single infections, leading to unfavorable patient outcomes. The interaction among microorganisms within polymicrobial infections has been shown to exacerbate disease progression. Polymicrobial infections, prevalent in various contexts such as the respiratory tract, wounds, and diabetic foot, typically involve diverse microorganisms, with Pseudomonas aeruginosa and Staphylococcus aureus being the most commonly identified pathogens. This study aimed to compare the growth patterns of bacteria under a concentration gradient of toxic chemicals, focusing on a Gram-negative strain of Pseudomonas aeruginosa and a Gram-positive strain of Staphylococcus aureus. The minimum inhibitory concentration (MIC), which signifies the concentration at which bacterial growth is inhibited, was determined by performing broth microdilution and assessing the bacteria's growth curves. The growth curves of both Pseudomonas aeruginosa and Staphylococcus aureus were confirmed, and the exponential growth phases were applied to calculate the doubling times of bacteria. The MIC value for each toxic chemical was determined through broth microdilution. These results allowed for the identification of disparities in growth rates between Gram-positive and Gram-negative bacteria, as well as differences in resistance to individual toxic substances. We expect that this approach has a strong potential for further development towards the innovative treatment of bacteria-associated infections.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.3
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• pp.155-163
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• 2023

Real-time monitoring technology is critical for ensuring the safety and reliability of nuclear power plant structures. However, the current seismic monitoring system has limited system identification capabilities such as modal parameter estimation. To obtain global behavior data and dynamic characteristics, multiple sensors must be optimally placed. Although several studies on optimal sensor placement have been conducted, they have primarily focused on civil and mechanical structures. Nuclear power plant structures require robust signals, even at low signal-to-noise ratios, and the robustness of each mode must be assessed separately. This is because the mode contributions of nuclear power plant containment buildings are concentrated in low-order modes. Therefore, this study proposes an optimal sensor placement methodology that can evaluate robustness against noise and the effects of each mode. Indicators, such as auto modal assurance criterion (MAC), cross MAC, and mode shape distribution by node were analyzed, and the suitability of the methodology was verified through numerical analysis.

• Conservation Science in Museum
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• v.4
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• pp.1-16
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• 2003

For the conservation treatment of the Central Asia mural painting which is to be exhibited in the new museum in Yongsan, we analyzed the pigments used in this mural painting and examined to identify the species of the straw in the wall. We also analyzed the species of the wood of the wooden protective frame and the material of the paper in it, in order to review the material and technique of the conservation treatment performed before the mural painting had been brought to the National Museum of Korea in 1916. The results were as follows: the black pigments of Bon4075 and Bon4078 is carbon(C); the white pigment on the background is gypsum[Ca(SO)₄(H₂O)₂]; the red pigment is lead oxide(Pb₃O₄) and hematite(Fe₂O₃) etc. The straw, which had been mixed into the wall to prevent the wall from cracking, was proved to be either wheat straw or oats straw. The wooden protective frame, which protects the mural painting now, was proved to be made of Salix, Populus, Cryptomeria japonica and pine. The paper discovered in the frame was proved to be made of the bark of a mulberry.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.401-408
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• 2023

The purpose of this study is to design textbook metadata as a basic task for building a textbook database. To this end, reading textbooks were defined as a category of textbooks, and a metadata development methodology was established through previous research. In order to ensure that bibliographically essential elements are not omitted, the catalog description elements of institutions that collect, accumulate, and service textbooks such as the National Library of Korea were investigated. The elements of Dublin Core, MODS, and KEM were mapped to derive elements suitable for describing textbooks. Finally, a set of textbook metadata elements consisting of 14 elements in three categories - bibliography, context, and textbook characteristics were presented by adding publication type, genre, and curriculum period elements. The 14 elements are titles, authors, publications, formats, identification sign, languages, locations, subject names, annotation, genres, table of contents, subjects, curriculum period, and curriculum information. In this study, we contributed to this field by discussing how to organize textbook resources with national knowledge resources, and in future studies, we proposed to evaluate usability by applying metadata elements to actual textbooks and revise and supplement them according to the evaluation results.

• The Journal of Bigdata
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• v.7 no.1
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• pp.213-224
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• 2022

In logistics and distribution, Market Basket Analysis (MBA) is used as an important means to analyze the correlation between major sales products and to increase internal operational efficiency. In particular, the results of market basket analysis are used as important reference data for decision-making processes such as product purchase prediction, product recommendation, and product display structure in stores. With the recent development of e-commerce, the number of items handled by a single distribution and logistics company has rapidly increased, And the existing analytical methods such as Apriori and FP-Growth have slowed down due to the exponential increase in the amount of calculation and applied to actual business. There is a limit to examining important association rules to overcome this limitation, In this study, at the Main-Category level, which is the highest classification system of products, the utility item set mining technique that can consider the sales volume of products together was used to first select a group of products mainly sold together. Then, at the sub-category level, the types of products sold together were identified using FP-Growth. By using this sequential layer filtering technique, it may be possible to reduce the unnecessary calculations and to find practically usable rules for enhancing the effectiveness and profitability.

• The Journal of Bigdata
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• v.7 no.1
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• pp.125-137
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• 2022

The transportation industry is one of the important industries due to the geographical requirements surrounded by the sea on three sides of Korea and the problem of resource poverty, which relies on imports for most of its resource consumption. Among them, the proportion of the shipping industry is large enough to account for most of the transportation industry, and maintenance in the shipping industry is also important in improving the operational efficiency and reducing costs of ships. However, currently, inspections are conducted every certain period of time for maintenance of ships, resulting in time and cost, and the cause is not properly identified. Therefore, in this study, the proposed methodology, LSTM-AutoEncoder, is used to detect abnormalities that may cause ship failure by considering the time of actual ship operation data. In addition, clustering is performed through clustering, and the potential causes of ship main engine failure are identified by grouping outlier by factor. This enables faster monitoring of various information on the ship and identifies the degree of abnormality. In addition, the current ship's fault monitoring system will be equipped with a concrete alarm point setting and a fault diagnosis system, and it will be able to help find the maintenance time.