• The Plant Pathology Journal
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• v.39 no.5
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• pp.486-493
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• 2023

Cowpea mild mottle virus (CPMMV) is a global plant virus that poses a threat to the production and quality of legume crops. Early and accurate diagnosis is essential for effective managing CPMMV outbreaks. With the advancement in isothermal recombinase polymerase amplification and lateral flow strips technologies, more rapid and sensitive methods have become available for detecting this pathogen. In this study, we have developed a reverse transcription recombinase polymerase amplification combined with lateral flow strips (RT-RPA-LFS) method for the detection of CPMMV, specifically targeting the CPMMV coat protein (CP) gene. The RT-RPA-LFS assay only requires 20 min at 40℃ and demonstrates high specificity. Its detection limit was 10 copies/µl, which is approximately up to 100 times more sensitive than RT-PCR on agarose gel electrophoresis. The developed RT-RPA-LFS method offers a rapid, convenient, and sensitive approach for field detection of CPMMV, which contribute to controlling the spread of the virus.

• The Plant Pathology Journal
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• v.40 no.3
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• pp.310-321
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• 2024

Tomato yellow leaf curl virus (TYLCV) and tomato spotted wilt virus (TSWV) are well-known examples of the begomovirus and orthotospovirus genera, respectively. These viruses cause significant economic damage to tomato crops worldwide. Weeds play an important role in the ongoing presence and spread of several plant viruses, such as TYLCV and TSWV, and are recognized as reservoirs for these infections. This work applies a comprehensive approach, encompassing field surveys and molecular techniques, to acquire an in-depth understanding of the interactions between viruses and their weed hosts. A total of 60 tomato samples exhibiting typical symptoms of TYLCV and TSWV were collected from a tomato greenhouse farm in Nonsan, South Korea. In addition, 130 samples of 16 different weed species in the immediate surroundings of the greenhouse were collected for viral detection. PCR and reverse transcription-PCR methodologies and specific primers for TYLCV and TSWV were used, which showed that 15 tomato samples were coinfected by both viruses. Interestingly, both viruses were also detected in perennial weeds, such as Rumex crispus, which highlights their function as viral reservoirs. Our study provides significant insights into the co-occurrence of TYLCV and TSWV in weed reservoirs, and their subsequent transmission under tomato greenhouse conditions. This project builds long-term strategies for integrated pest management to prevent and manage simultaneous virus outbreaks, known as twindemics, in agricultural systems.

• Journal of Animal Science and Technology
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• v.66 no.4
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• pp.781-791
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• 2024

Bovine viral diarrhea (BVD) is a single-stranded, positive-sense ribonucleic acid (RNA) virus belonging to the genus Pestivirus of the Flaviviridae family. BVD frequently causes economic losses to farmers. Among bovine viral diarrhea virus (BVDV) strains, BVDV-1b is predominant and widespread in Hanwoo calves. Reverse-transcription polymerase chain reaction (RT-PCR) is an essential method for diagnosing BVDV-1b and has become the gold standard for diagnosis in the Republic of Korea. However, this diagnostic method is time-consuming and requires expensive equipment. Therefore, Clustered regularly interspaced short palindromic repeats-Cas (CRISPR-Cas) systems have been used for point-of-care (POC) testing of viruses. Developing a sensitive and specific method for POC testing of BVDV-1b would be advantageous for controlling the spread of infection. Thus, this study aimed to develop a novel nucleic acid detection method using the CRISPR-Cas13 system for POC testing of BVDV-1b. The sequence of the BVD virus was extracted from National Center for Biotechnology Information (NC_001461.1), and the 5' untranslated region, commonly used for detection, was selected. CRISPR RNA (crRNA) was designed using the Cas13 design program and optimized for the expression and purification of the LwCas13a protein. Madin Darby bovine kidney (MDBK) cells were infected with BVDV-1b, incubated, and the viral RNA was extracted. To enable POC viral detection, the compatibility of the CRISPR-Cas13 system was verified with a paper-based strip through collateral cleavage activity. Finally, a colorimetric assay was used to evaluate the detection of BVDV-1b by combining the previously obtained crRNA and Cas13a protein on a paper strip. In conclusion, the CRISPR-Cas13 system is highly sensitive, specific, and capable of nucleic acid detection, making it an optimal system for the early point-of-care testing of BVDV-1b.

• Journal of the Korean Society of Safety
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• v.22 no.4
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• pp.102-109
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• 2007

A bioterrorism attack is the deliberate release of viruses, bacteria, or other germs(agents) used to cause illness or death in people, animals, or plant. These agents are found in nature, but it is possible that they could be changed to increase their ability to cause disease, make them resistant to current medicines, or to increase their ability to be spread into the environment. Terrorists may use biological agents because these agents can be extremely difficult to detect and do not cause illness for several days. Some bioterrorism agents, like smallpox virus, can spread from person to person, like anthrax, can not. From these agents, we discussed the characteristics of biological agents and national safety regulation on the weapons of mass destruction including bioterrorism.

• Journal of the Society of Disaster Information
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• v.3 no.2
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• pp.119-128
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• 2007

A bioterrorism attack is the deliberate release of viruses, bacteria, or other agents used to cause illness or death in people, animals, or plant. These agents are found in nature, but it is possible that they could be changed to increase their ability to cause disease, make them resistant to current medicines, or to increase their ability to be spread into the environment. Terrorists may use biological agents because these agents can be extremely difficult to detect and do not cause illness for several days. Some bioterrorism agents, like smallpox virus, can spread from person to person, like anthrax, can not. From these agents, we discussed the characteristics of biological agents and national safety regulation on the weapons of mass destruction including bioterrorism.

• Journal of Multimedia Information System
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• v.8 no.4
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• pp.251-258
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• 2021

In 2019, a novel coronavirus (COVID-19) outbreak started in China and spread all over the world. The countries went into lockdown and closed their borders to minimize the spread of the virus. Shortage of testing kits and trained clinicians, motivate researchers and computer scientists to look for ways to automatically diagnose the COVID-19 patient using X-ray and ease the burden on the healthcare system. In recent years, multiple frameworks are presented but most of them are trained on a very small dataset which makes clinicians adamant to use it. In this paper, we have presented a lightweight deep learning base automatic COVID-19 detection system. We trained our model on more than 22,000 dataset X-ray samples. The proposed model achieved an overall accuracy of 96.88% with a sensitivity of 91.55%.

• Journal of Korea Multimedia Society
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• v.22 no.6
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• pp.684-694
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• 2019

Information spread in networks is universal in many real-world phenomena such as propagation of infectious diseases, diffusion of a new technology, computer virus/spam infection in the internet, and tweeting and retweeting of popular topics. The problem of finding the information source is to pick out the true source if information spread. It is of practical importance because harmful diffusion can be mitigated or even blocked e.g., by vaccinating human or installing security updates. This problem has been much studied, where it has been shown that the detection probability cannot be beyond 31% even for regular trees if the number of infected nodes is sufficiently large. In this paper, we study the impact of an anti-information spreading on the original information source detection. We consider an active defender in the network who spreads the anti-information against to the original information simultaneously and propose an inverse Voronoi partition based inference approach, called Voronoi Inference to find the source. We perform various simulations for the proposed method and obtain the detection probability that outperforms to the existing prior work.

• Annual Conference of KIPS
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• 2021.11a
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• pp.647-650
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• 2021

The most powerful and modern face recognition techniques are using deep learning methods that have provided impressive performance. The outbreak of COVID-19 pneumonia has spread worldwide, and people have begun to wear a face mask to prevent the spread of the virus, which has led existing face recognition methods to fail to identify people. Mainly, it pushes masked face recognition has become one of the most challenging problems in the face recognition domain. However, deep learning methods require numerous data samples, and it is challenging to find benchmarks of masked face datasets available to the public. In this work, we develop a new simulated masked face dataset that we can use for masked face recognition tasks. To evaluate the usability of the proposed dataset, we also retrained the dataset with ArcFace based system, which is one the most popular state-of-the-art face recognition methods.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.93-102
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• 2021

The world is facing an unprecedented economic, social and political crisis with the spread of COVID-19. The Corona Virus (COVID-19) and its global spread have resulted in declaring a pandemic by the World Health Organization. The deadly pandemic of 21st century has spread its wings across the globe with an exponential increase in the number of cases in many countries. The developing and underdeveloped countries are struggling hard to counter the rapidly growing and widespread challenge of COVID-19 because it has greatly influenced the global economies whereby the underdeveloped countries are more affected by its devastating impacts, especially the life of the low-income population. Information and Communication Technology (ICT) were particularly useful in spreading key emergency information and helping to maintain extensive social distancing. Updated information and testing results were published on national and local government websites. Mobile devices were used to support early testing and contact tracing. The government provided free smartphone apps that flagged infection hotspots with text alerts on testing and local cases. The purpose of this research work is to provide an in depth overview of emerging technologies and recent ICT developments to combat COVID-19 Pandemic. Finally, the author highlights open challenges in order to give future research directions.

• Journal of IKEEE
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• v.26 no.4
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• pp.681-685
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• 2022

Including the COVID-19 crisis, humanity is constantly exposed to viral infections, and efforts are being made to prevent the spread of infection by quickly isolating infected people and tracing contacts. Passive epidemiological investigations that confirm contact with an infected person through contact have limitations in terms of accuracy and speed, so automatic tracking methods using various digital technologies are being proposed. This paper verify contact by utilizing Bluetooth Low Energy (BLE) technology and present an algorithm that identifies close contact through analysis and correction of RSSI (Received Signal Strength Indicator) values. Also, propose a system that can prevent the spread of viruses in a centralized server structure.