• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.107-112
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• 2024

Nowadays the deadly virus famous as COVID-19 spread all over the world starts from the Wuhan China in 2019. This disease COVID-19 Virus effect millions of people in very short time. There are so many symptoms of COVID19 perhaps the Identification of a person infected with COVID-19 virus is really a difficult task. Moreover it's a challenging task to identify whether a person or individual have covid test positive or negative. We are developing a framework in which we used machine learning techniques..The proposed method uses DecisionTree, KNearestNeighbors, GaussianNB, LogisticRegression, BernoulliNB , RandomForest , Machine Learning methods as the classifier for diagnosis of covid ,however, 5-fold and 10-fold cross-validations were applied through the classification process. The experimental results showed that the best accuracy obtained from Decision Tree classifiers. The data preprocessing techniques have been applied for improving the classification performance. Recall, accuracy, precision, and F-score metrics were used to evaluate the classification performance. In future we will improve model accuracy more than we achieved now that is 93 percent by applying different techniques

• Journal of Preventive Medicine and Public Health
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• v.53 no.5
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• pp.293-301
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• 2020

Objectives: At the beginning of the coronavirus disease 2019 (COVID-19) pandemic, some countries imposed entry bans against Chinese visitors. We sought to identify the effects of border shutdowns on the spread of the COVID-19 outbreak. Methods: We used the synthetic control method to measure the effects of entry bans against Chinese visitors on the cumulative number of confirmed cases using World Health Organization situation reports as the data source. The synthetic control method constructs a synthetic country that did not shut down its borders, but is similar in all other aspects. Results: Six countries that shut down their borders were evaluated. For Australia, the effects of the policy began to appear 4 days after implementation, and the number of COVID-19 cases dropped by 94.4%. The border shutdown policy took around 13.2 days to show positive effects and lowered COVID-19 cases by 91.7% on average by the end of February. Conclusions: The border shutdowns in early February significantly reduced the spread of the virus. Our findings are informative for future planning of public health policies.

• The Journal of the Korean dental association
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• v.54 no.1
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• pp.67-83
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• 2016

Ebola virus disease is a lethal viral hemorrhagic fever that has been boiling in sub-Saharan Africa since 1970s. Last year, The Ebola virus epidemic that has spread not only mainly in West Africa, but also in locals such as USA, Europe and the Antipodes via infected travelers, was brought up. Human-to-human transmission of Ebola virus disease is known only through direct contact with the blood, secretions, tissues or other bodily fluids, including saliva. Although there has not been reported infection cases in the dental healthcare settings, the fact that the infection of the Ebola virus may be made from human secretions such as saliva suggests that there is a high risk of infection for the Ebola virus of dental healthcare workers. Therefore, it is important dental healthcare workers to identify infection-suspected patients through the oral findings for infection prevention. This article will review the oral signs and symptoms of Ebola virus disease and discuss the pathogenesis, treatment and prevention. Furthermore, Infection control guidelines for oral healthcare workers are also proposed.

• Korean Journal of Veterinary Service
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• v.46 no.3
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• pp.193-202
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• 2023

Porcine epidemic diarrhea is an infectious intestinal disease caused by the porcine epidemic diarrhea virus (PEDV). Especially, when suckling piglets are infected, the mortality rate is close to 100%. PEDV is classified into G1 and G2 types based on genetic differences. The G2 type PEDV outbreak in the United States in 2013 was highly pathogenic and contagious, and it has spread worldwide and caused continuous economic losses. Most commercial vaccines used are G1 type vaccines, and existing vaccines do not fully protect piglets due to genetic differences. In this study, we evaluated the safety of the newly developed G2 type attenuated HSGP vaccine strain by inoculating it into piglets and testing whether the vaccine virus spreads to the non-vaccinated, negative pigs and whether the vaccine reverts to its virulence during serial passage experiments. Each experiment lasted for 7 days for each passage, and fecal viral titers, clinical symptoms, and weight gain were measured daily. After the experiment, necropsy was performed to measure intestinal virus titer and pathological evaluation. As a result of the first passage, no transmission of the vaccine virus to negative pigs co-housed with vaccinated pigs was observed. In addition, after four consecutive passage experiments, the clinical symptoms and small intestine lesions were gradually alleviated, and no virus was detected in the feces in the fourth passage experiment. Therefore, it was concluded that the vaccine was safe without virulence reversion in accordance with the guidelines of the current licensing authority. However, further studies are needed on the genetic changes and biological characteristics of the mutant virus that occur during successive passages of the attenuated vaccine since the replication and clinical symptoms of the virus increased until the third passage during successive passages of the vaccine virus. Based on this study, it was concluded that virulence reversion and safety evaluation of attenuated vaccines through serial passage in target animals can be useful to evaluate the safety of attenuated viruses.

• Journal of Microbiology and Biotechnology
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• v.33 no.12
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• pp.1576-1586
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• 2023

Vaccination is the most effective method for preventing the spread of the influenza virus. Cell-based influenza vaccines have been developed to overcome the disadvantages of egg-based vaccines and their production efficiency has been previously discussed. In this study, we investigated whether treatment with forskolin (FSK), an adenylyl cyclase activator, affected the output of a cell-based influenza vaccine. We found that FSK increased the propagation of three influenza virus subtypes (A/H1N1/California/4/09, A/H3N2/Mississippi/1/85, and B/Shandong/7/97) in Madin-Darby canine kidney (MDCK) cells. Interestingly, FSK suppressed the growth of MDCK cells. This effect could be a result of protein kinase A (PKA)-Src axis activation, which downregulates extracellular signal-regulated kinase (ERK)1/2 activity and delays cell cycle progression from G1 to S. This delay in cell growth might benefit the binding and entry of the influenza virus in the early stages of viral replication. In contrast, FSK dramatically upregulated ERK1/2 activity via the cAMP-PKA-Raf-1 axis at a late stage of viral replication. Thus, increased ERK1/2 activity might contribute to increased viral ribonucleoprotein export and influenza virus propagation. The increase in viral titer induced by FSK could be explained by the action of cAMP in assisting the entry and binding of the influenza virus. Therefore, FSK addition to cell culture systems could help increase the production efficiency of cell-based vaccines against the influenza virus.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.195-201
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• 2024

With the Covid-19(Corona Virus) spread all around the world, people are using this propaganda and the desperate need of the citizens to know the news about this mysterious virus by spreading fake news. Some Countries arrested people who spread fake news about this, and others made them pay a fine. And since Social Media has become a significant source of news, .there is a profound need to detect these fake news. The main aim of this research is to develop a web-based model using a combination of machine learning algorithms to detect fake news. The proposed model includes an advanced framework to identify tweets with fake news using Context Analysis; We assumed that Natural Language Processing(NLP) wouldn't be enough alone to make context analysis as Tweets are usually short and do not follow even the most straightforward syntactic rules, so we used Tweets Features as several retweets, several likes and tweet-length we also added statistical credibility analysis for Twitter users. The proposed algorithms are tested on four different benchmark datasets. And Finally, to get the best accuracy, we combined two of the best algorithms used SVM ( which is widely accepted as baseline classifier, especially with binary classification problems ) and Naive Base.

• Korean Journal of Veterinary Service
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• v.35 no.4
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• pp.333-337
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• 2012

This study was carried out to investigate the prevalence of bovine leukemia virus (BLV) infection and to compare the results of enzyme-linked immunosorbent assay (ELISA) and nested polymerase chain reaction (nPCR) in dairy farms in northern Gyeonggi province from August through December 2011. A total of 625 dairy cattle from 14 dairy farms were tested for antibodies against BLV using commercially available ELISA test kit. The overall seroprevalence of BLV infection was 76.3%. The seroprevalence of diary cattle according to age was the highest at 61~72 months (88.0%, P<0.001). Two hundred fifty one dairy cattle from 7 diary farms were tested ELISA and nPCR. The kappa value of BLV between ELISA and nPCR was 0.765. The results indicate that BLV infection spread widely in dairy farms and the nPCR is rapid method for the early detection of BLV infection.

• Korean Journal of Veterinary Service
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• v.38 no.1
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• pp.13-17
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• 2015

Three serotypes (O, A and Asia1) of the foot-and-mouth disease (FMD) vaccine were injected into domestic cloven-hoofed animals in korea after the nationwide spread at the end of 2010. The purpose of this study was survey of FMD virus stuructural protein (SP) antibody titer in Yeongcheon by enzyme-linked immunosorbent assay (ELISA). Total 1,324 samples collected from 89 farms were tested. The overall seroprevalence of FMD virus SP antibodies was 58.8% (778/1,324) The seroprevalence of FMD virus SP antibody varied with species. Results in cattle (over 12 month old) and pig (90 to 130 day old) were 58.8% and 44.9% respectively.

• Korean Journal of Veterinary Service
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• v.30 no.2
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• pp.197-203
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• 2007

A total of 501 serum samples were selected from blood samples that were submitted to Department of Veterinary Pathology, Kangwon National University from all provinces in Korea from September 2001 to August 2002. Their sera were examined for antibodies to swine influenza virus subtype H1N1 (SlV H1N1) and porcine repro-ductive and respiratory syndrome virus (PRRSV) according to the age of pig, season, and herd size using enzyme-linked immunosorbent assay. The seroprevalence of SIV H1N1, PRRSV, and dual infection were 39.12%, 61.48%, and 25.95%, respectively. The seroprevalence of SIV H1N1 according to herd size was not significant differences (p>0.05). The results showed that the PRRSV infection spread widely in swine herds throughout the country.

• Research in Plant Disease
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• v.28 no.2
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• pp.92-97
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• 2022

Apple stem grooving virus (ASGV) is a high-risk viral pathogen that infects many types of fruit trees, especially pear and apple, and causes serious economic losses across the globe. Thus, rapid and reliable detection assay is needed to identify ASGV infection and prevent its spread. A reliable reverse transcription loop-mediated isothermal amplification (RT-LAMP) was developed, optimize, and evaluated for the coding region of coat protein of ASGV in pear leaf. The developed RT-LAMP facilitated the simple screening of ASGV using visible fluorescence and electrophoresis. The optimized reaction conditions for the RT-LAMP were 63℃ for 50 min, and the results showed high specificity and 100-fold greater sensitivity than the reverse transcription polymerase chain reaction. In addition, the reliability of the RT-LAMP was validated using field-collected pear leaves. Furthermore, the potential application of paper-based RNA isolation, combined with RT-LAMP, was also evaluated for detecting ASGV from field-collected samples. These assays could be widely applied to ASGV detection in field conditions and to virus-free certification programs.