• Journal of Distribution Science
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• v.18 no.11
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• pp.41-45
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• 2020

Purpose: This article aims to explore the new town development paradigm against infectious diseases. The distribution of COVID-19 constricts economic activity. The high frequency of outbreaks of COVID-19 nationwide is due to neither malnutrition nor unhygienic environment. Research design, data and methodology: The research question starts with the idea that understanding the features of the outbreak of pandemic diseases could help public health authorities to better cope with upcoming risks in the future. We have employed a big data-based methodology to explore the outbreak of pandemic diseases. Also, an idiographic approach is used to describe the distribution of new towns against COVID-19. Results: The results demonstrate that the rapid spread of COVID-19 has had a strong impact on regional economies and urban development. It was found that there is a close relationship between infectious diseases outbreaks and new town development. Conclusions: The findings could be used to deal with new town development against infectious diseases better in other cities or countries as well. The distribution of COVID-19 may become an unexpected opportunity for a paradigm shift in the distribution of new town development to prevent not only an excessive concentration in Seoul, but also an imbalance between national and local development.

• Tuberculosis and Respiratory Diseases
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• v.84 no.1
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• pp.22-34
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• 2021

The coronavirus pandemic, known as coronavirus disease 2019 (COVID-19), is an infectious respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus first identified in patients from Wuhan, China. Since December 2019, SARS-CoV-2 has spread swiftly around the world, infected more than 25 million people, and caused more than 800,000 deaths in 188 countries. Chronic respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD) appear to be risk factors for COVID-19, however, their prevalence remains controversial. In fact, studies in China reported lower rates of chronic respiratory conditions in patients with COVID-19 than in the general population, while the trend is reversed in the United States and Europe. Although the underlying molecular mechanisms of a possible interaction between COVID-19 and chronic respiratory diseases remain unknown, some observations can help to elucidate them. Indeed, physiological changes, immune response, or medications used against SARS-CoV-2 may have a greater impact on patients with chronic respiratory conditions already debilitated by chronic inflammation, dyspnea, and the use of immunosuppressant drugs like corticosteroids. In this review, we discuss importance and the impact of COVID-19 on asthma and COPD patients, the possible available treatments, and patient management during the pandemic.

• Journal of fish pathology
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• v.23 no.1
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• pp.99-106
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• 2010

Aquatic animal diseases control act which is to assure the prevention of outbreak and spread of aquatic animal diseases in Korea has come into effect since 22 December 2008. In order to prevent outbreak and spread of aquatic animal diseases, risk analysis is newly introduced. The introduction of risk analysis for movement of aquatic animals related to implementation of recommendation of the World Trade Organization (WTO) Agreement on the Application of Sanitary and Phytosanitary Measures and should be conducted in accordance with guidelines of OIE Aquatic Animal Health Code. This report involves gathering and analysing the information of international regulation and situations of risk analysis framework in Korea for movement of aquatic animals.

• Smart Media Journal
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• v.9 no.3
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• pp.122-129
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• 2020

The possibility that an asymptotic coronavirus-19 infected person around the world is not aware of his infection and can spread it to people around him is still a very important issue in that the public is not free from anxiety and fear over the spread of the epidemic. In this paper, the K-means clustering algorithm and deep learning-based crowd aggregation were proposed to determine the possibility of contact with confirmed cases of infectious diseases. As a result of 300 iterations of all input learning images, the PSNR value was 21.51, and the final MAE value for the entire data set was 67.984. This means the average absolute error between observations and the average absolute error of fewer than 4,000 people in each CCTV scene, including the calculation of the distance and infection rate from the confirmed patient and the surrounding persons, the net group of potential patient movements, and the prediction of the infection rate.

• Smart Media Journal
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• v.11 no.4
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• pp.62-68
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• 2022

To prevent the spread of disease in aquaculture, it is a need for a system to predict fish diseases while monitoring the water quality environment and the status of growing fish in real time. The existing research in predicting fish disease were image processing techniques. Recently, there have been more studies on disease prediction methods through deep learning techniques. This paper introduces the research results on how to predict diseases of Paralichthys Olivaceus with deep learning technology in aquaculture. The method enhances the performance of disease detection rates by including data augmentation and pre-processing in camera images collected from aquaculture. In this method, it is expected that early detection of disease fish will prevent fishery disasters such as mass closure of fish in aquaculture and reduce the damage of the spread of diseases to local aquaculture to prevent the decline in sales.

• Journal of Korean Society of Forest Science
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• v.95 no.3
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• pp.240-249
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• 2006

Recently, dispersion of damaged forest by pine wilt disease has been regarded as a serious social issue. Damages by pine wilt disease have been spreaded by natural area expansion of the vectors in the damaged area, while the national wide damage spread has induced by human-involved carrying infected trees out of damaged area. In this study, damaged trees were detected and located on the digital map by aerial photograph and terrestrial surveys. The spatial distribution pattern of damaged trees, and the relationship of spatial distribution of damaged trees and some geomorphological factors were geostatistically analysed. Finally, we maked natural spread pattern map of pine wilt disease using geostatistical CART(Classification and Regression Trees) model. This study verified that geostatistical analysis and CART model are useful tools for understanding spatial distribution and natural spread pattern of pine wilt diseases.

• Korean Journal of Veterinary Service
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• v.35 no.2
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• pp.111-117
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• 2012

This study investigated the occurrence of honeybee diseases in Incheon area, at the point of great widespread of sacbrood disease in the country. Sixteen resident beekeeping apiaries; 3 native honeybee and 13 European honeybee apiaries were selected for this research. Over 20 adult bees were evenly collected from the most colonies of each apiary three times (March, June, November) within a year. In this work, 13 honeybee diseases including 7 viral diseases, 2 bacterial diseases, 2 fungal diseases, and 2 parasitic diseases were detected by preliminary inspections and PCR. As a result, viral infections were confirmed at 34 among 48 apiaries (70.8%) over the entire examination period. Parasitic diseases showed the highest detection rate of 45.8%, which are detected in 44 among 96 cases. In the seasonal prevalence, 30 cases (15.6%) of 7 pathogens were detected from 14 apiaries in March, 50 cases (24.0%) of 9 pathogens and 56 cases (26.9%) of 9 pathogens were detected from all apiaries in June and November, respectively. Nosema was shown to be the most prevalent pathogen from March to November, followed by sacbrood virus (SBV) and stonebrood. The spread of SBV infection in Incheon would be under-estimated by the increasing of detection rate over the time. Especially, Chinese sacbrood virus was detected from 4 European honybee apiaries, but clinical symptoms were not found. No chalkbrood, acute bee paralysis virus, and chronic bee paralysis virus were detected in this study. The effective therapy and preventive measures should be prepared for beekeeping industry.

• Childhood Kidney Diseases
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• v.10 no.2
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• pp.249-256
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• 2006

Diarrhea-associated hemolytic uremic syndrome(D+ HUS) is induced by enterohemorrhagic Escherichia coli(EHEC) and is characterized by the triad of microangiopathic hemolytic anemia, thrombocytopenia, and acute renal failure. The disease is usually transmitted by meat and water contaminated by excreta of domestic animals. We report a son and his mother with diarrhea-associated hemolytic uremic syndrome that spread within the family.

• Journal of Korean Physical Therapy Science
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• v.10 no.2
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• pp.236-245
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• 2003

As one of the effective therapies for musculoskeletal diseases, orthopedic manual physical therapy has been watched with keen interest. In Korea, orthopedic manual physical therapy has been widely spread and applied in the field of clinical medicine since the mid-nineties. Since then, the clinical efficacy of orthopedic manual physical therapy has been approved, and orthopedic manual physical therapy has been gradually spread in the filed of clinical medicine. However, it should be noted that clinically available therapies are not well recognized. Therefore, this study was conducted to allude diagnostic and therapeutic characteristics of these therapies including deep tissue massage, manual therapy, Cyriaxs method combining manual reduction and chemotherapy, Kaltenborn-Evjenth method based on concave-convex rule for joint and soft tissue, Maitlands method based on patients sign and symptom, stress due to the posture, intraarticualr disturbance and Mckenzies method for pain due to the dysfunction.

• 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.