• Journal of the Korea Convergence Society
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• v.11 no.7
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• pp.19-24
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• 2020

WHO declared a global pandemic on March 11th for Corona 19. However, there is a situation where you have to go to building for face-to-face education or seminars for economic and social activities. The first check method of COVID-19 infection is to measure body temperature, so the primary entrance and exit is blocked for near-field body temperature measurement. However, since it is troublesome to check directly, thermal camera is installed at the entrance of the building, and body temperature is measured indirectly using the infrared camera to control access. In case of middle and high schools, universities, and lifelong education center, we need a system that is possible to interoperate with attendance checks and automatically recognizes whether to wear masks and can authenticate students. We proposed the system that is to confirm whether to wear a mask with a camera that is embedded in a smart mirror, and that authenticates the user through voice recognition of the user who wants to enter the building by using voice recognition technology and determines whether to enter them or not. The proposed system can check attendance if it is linked with near-field temperature measurement and attendance check APP of student's smart phone.

• Proceedings of the Korea Contents Association Conference
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• 2015.05a
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• pp.223-224
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• 2015

구제역은 소, 돼지 등 발굽이 두 개로 갈라진 가축들에게 감염을 유발하는 전염성이 매우 높은 바이러스성 질병이다. 구제역 감염 시 입 주변, 구강 내, 코, 발굽사이 등에 수포가 생기며 고열과 식욕이 저하되어 심하게 앓거나 죽게 되는데, 강한 감염 전파력을 가졌음에도 치료제가 없고, 감염확인 즉시 확산 방지를 위한 살 처분만이 이루어지고 있다. 따라서 무엇보다도 빠른 감염여부 진단이 중요하다. 현재까지 구제역을 진단하는 방법으로는 감염 된 가축의 혈액에서 구제역 항원 단백질에 대한 항체형성 여부를 확인하는 항체진단법과 수포액과 같은 체액을 채취하여 세포배양을 통한 구제역 바이러스 분리방법이 있지만 두 가지 모두 짧은 잠복기를 갖는 구제역 바이러스를 빠른 시간 내 진단하기는 어렵다. 따라서 본 연구에서는 보다 빠른 구제역 진단 키트개발을 위해 NCBI Pubmed를 이용하여 구제역바이러스가 가지는 6개의 주요 단백질을 확인하였고, NCBI BLAST를 이용하여 6개의 단백질 중 구제역 바이러스에 특이적인 항원 단백질 peptidase C28을 선정하였다. 선정된 단백질의 아미노산 서열을 이용하여 IEDB analysis resource를 통해 peptidase C28의 epitope 부위를 예측하였다. 예측 된 부위의 아미노산 서열을 NCBI BLAST에서 정상 동물과 비교하여 구제역바이러스 특이 항원 단백질 epitope peptide를 최종 선정하였다. 이를 이용한 구제역 바이러스 진단키트 제작은 보다 빠른 진단을 통해 감염 확산을 조기에 차단하고 경제적 손실과 피해를 최소화 할 수 있다.

• Research in Plant Disease
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• v.23 no.1
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• pp.1-18
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• 2017

Pseudomonas syringae pv. actinidiae, the causal agent of bacterial canker, is currently causing severe economic losses to kiwifruit production worldwide. The pathogen has affected green-fleshed kiwifruit cutlivars and yellow-fleshed kiwifruit cultivars since 1988 and 2006 in Korea, respectively. In recent years, the biovar 3 strains of P. syringae pv. actinidiae were introduced through imported contaminated pollens and have rapidly spread to neighboring kiwiruit orchards by secondary infection, leading to outbreaks of bacterial canker and tremendous damages on yellow- and red-fleshed kiwifruit cultivars. In this review, we summarize the various management practices of bacterial canker of kiwifruit such as disease escaping, cultural practices, blocking of dissemination, early diagnosis, eradication of inoculum sources, chemical control, and trunk injection on the basis of our research works and field experiences and important research products conducted during the last three decades in the world. Finally, we propose a manual for the efficient management of the disease that can be practically utilized at the farmers' orchards in order to keep kiwifruit vines healthy in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.186-198
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• 2016

HPAI(Highly Pathogenic Avian Influenza) is a contagious animal disease that spreads rapidly by diffusion after the first occurrence. The disease has brought tremendous social costs and economic losses. KAHIS (Korea Animal Health Information System) is the integrated system for supporting the task of preventing epidemics. They provide decision-support information, recording vehicle visiting times and facility location, etc., which is possible by enforcing registration of all livestock related facilities and vehicles. KAHIS has accumulated spatial and temporal information that enables effective tracing of potential disease trajectories and diffusion through vehicle movements. The contact network is created utilizing spatial and temporal information in KAHIS to inform facility connection via vehicle visitation. Based on the contact network, it is possible to infer spatial and temporal mechanism of disease spread and diffusion. The study objective is to empirically demonstrate how to utilize primary spatial and temporal information in KAHIS in the form of the contact network. Based on the contact network, facilities with the possibility of infection can be pinpointed within the potential spatial and temporal extent where the disease has spread and diffused. This aids the decision-making process in the task of preventing epidemics. By interpreting our demonstration results, policy implications were presented. Finally, some suggestions were made to comprehensively utilize the contact network to draw enhanced decision-support information.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.45-51
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• 2022

Fear of contact exists due to the prevention of the spread of infectious diseases such as COVID-19. When using the common entrance door of an apartment, access is possible only if the resident enters a password or obtains the resident's permission. There is the inconvenience of having to manually enter the number and password for the common entrance door to enter. Also, contactless entry is required due to COVID-19. Due to the development of ICT, users can be easily identified through the development of face recognition and voice recognition technology. The proposed method detects a visitor's face through a CCTV or camera attached to the common entrance door, recognizes the face, and identifies it as a registered resident. Then, based on the registered information of the resident, it is possible to operate without contact by interworking with the elevator on the server. In particular, if face recognition fails with a hat or mask, the visitor is identified by voice or additional authentication of the visitor is performed based on the voice message. It is possible to block the spread of contagiousness without leaving any contactless function and fingerprint information when entering and exiting the front door of an apartment house, and without the inconvenience of access.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.57-78
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• 2023

COVID-19, which started in Wuhan, China in November 2019, spread beyond China in 2020 and spread worldwide in March 2020. It is important to prevent a highly contagious virus like COVID-19 in advance and to actively treat it when confirmed, but it is more important to identify the confirmed fact quickly and prevent its spread since it is a virus that spreads quickly. However, PCR test to check for infection is costly and time consuming, and self-kit test is also easy to access, but the cost of the kit is not easy to receive every time. Therefore, if it is possible to determine whether or not a person is positive for COVID-19 based on the sound of a cough so that anyone can use it easily, anyone can easily check whether or not they are confirmed at anytime, anywhere, and it can have great economic advantages. In this study, an experiment was conducted on a method to identify whether or not COVID-19 was confirmed based on a cough sound. Cough sound features were extracted through MFCC, Mel-Spectrogram, and spectral contrast. For the quality of cough sound, noisy data was deleted through SNR, and only the cough sound was extracted from the voice file through chunk. Since the objective is COVID-19 positive and negative classification, learning was performed through XGBoost, LightGBM, and FCNN algorithms, which are often used for classification, and the results were compared. Additionally, we conducted a comparative experiment on the performance of the model using multidimensional vectors obtained by converting cough sounds into both images and vectors. The experimental results showed that the LightGBM model utilizing features obtained by converting basic information about health status and cough sounds into multidimensional vectors through MFCC, Mel-Spectogram, Spectral contrast, and Spectrogram achieved the highest accuracy of 0.74.