• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.514-522
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• 2022

Non-destructive testing (NDT) technology is a widely used inspection method for agricultural products. Compared with the conventional inspection method, there is no extensive sample preparation for NDT technology, and the sample is not damaged. In particular, NDT technology is used to inspect the internal structure of agricultural products infested by pests. The introduction and spread of pests during the import and export process can cause significant damage to the agricultural environment. Until now, pest detection in agricultural products and quarantine processes have been challenging because they used external inspection methods. However, NDT technology is advantageous in these inspection situations. In this pilot study, we investigated the feasibility of X-ray computed tomography (X-ray CT) and magnetic resonance imaging (MRI) to identify pest infestation in agricultural products. Three kinds of artificially pest-infested fruits (mango, tangerine, and chestnut) were non-destructively inspected using X-ray CT and MRI. X-ray CT was able to identify all pest infestations in fruits, while MRI could not detect the pest-infested chestnut. In addition, X-ray CT was superior to the quarantine process than MRI based on the contrast-to-noise ratio (CNR), image acquisition time, and cost. Therefore, X-ray CT is more appropriate for the pest quarantine process of fruits than MRI.

• Journal of Forest and Environmental Science
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• v.38 no.2
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• pp.128-132
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• 2022

Wild boars (Sus scrofa) not only cause crop damage and human casualties, but also facilitate the spread of many infectious diseases in domestic animals and humans. To determine the efficiency of a fencing system in blocking the movement of wild boars, long-term monitoring was performed in a fenced area in Bukhansan National Park using camera traps. Upon monitoring for a period of 46 months, there was a 72.6% reduction in the number of wild boar appearances in the fence-enclosed area, compared to that in the unenclosed area. For 20 months after the fence installation, the blocking effect of the fence was effective enough to reduce the appearance of wild boars by 92.6% in the fence-enclosed area, compared to that in the unenclosed area. The blocking effect of the fence remained effective for 20 months after its installation, after which its effectiveness decreased. Maintaining a fence for a long time is likely to lead to habitat fragmentation. It can also block the movement of other wild animals, including the endangered species - the long-tailed goral. This study suggests a 20-month retention period for the fences installed to inhibit the movement of wild boars in wide forests such as Gangwon-do in South Korea. To identify how long the blocking effect of the fences lasts, further studies are needed focusing on the length and height of the fence, and the conditions of the ground surface.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.591-597
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• 2022

As social anxiety is increasing due to the spread of the COVID-19 epidemic, the responses at the level of local governments are also changing depending on the characteristics. We analyzed the factors influencing perceptions of social safety as they relate to the trustworthiness of local governments. Based on a 2020 social survey of 16 cities, counties, and districts in Busan Metropolitan City, the effects of householder characteristics, economic characteristics, local attachment characteristics, and social safety perception characteristics on the reliability of the local government were analyzed through an ordinal logistic regression analysis. It was found that the more vulnerable the class was and the safer the region was, the higher the trust was in the basic local government. In order to respond and preemptively recover damage in natural and social disaster situations, continuous efforts are needed to strengthen the capabilities of basic local governments.

• Smart Media Journal
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• v.11 no.5
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• pp.48-55
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• 2022

Tomato crops are easy to expose to disease and spread in a short period of time, so late measures against disease are directly related to production and sales, which can cause damage. Therefore, there is a need for a service that enables early prevention by simply and accurately diagnosing tomato diseases in the field. In this paper, we construct a system that applies a deep learning-based model in which ImageNet transition is learned in advance to classify and serve nine classes of tomatoes for disease and normal cases. We use the input of MobileNet, ResNet, with a deep learning-based CNN structure that builds a lighter neural network using a composite product for the image set of leaves classifying tomato disease and normal from the Plant Village dataset. Through the learning of two proposed models, it is possible to provide fast and convenient services using MobileNet with high accuracy and learning speed.

• International Journal of High-Rise Buildings
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• v.10 no.4
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• pp.311-321
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• 2021

Perception of the public to structural fires is very important because there are only a number of tall timber buildings constructed in the world. People are hesitating to accept tall timber buildings, so it is essential to ensure the first generation of tall timber buildings to a very high standard, especially fire safety. Right now, there are no specific design standards or regulations for fire design of tall timber buildings in Europe. Even though heavy timber members have better fire resistance than steel components, many conditions still need to be verified before considering the use of timber materials, e.g. fire spread, post-fire collapse, etc. This research numerically explores the structural behaviours of a tall Glulam building when one of its internal Glulam (Glued laminated timber) columns fails after sustaining a full 120-min standard fire and is removed from the established finite element building model created in SAP2000. The numerical results demonstrate that the failure and removal of the selected internal Glulam column may lead to the local failure of the adjacent CLT (Cross laminated timber) floor slabs, but will not lead to large disproportionate damage and collapse of the whole building. Here, the building is assumed to be located in Glasgow, Scotland, UK.

• Journal of Advanced Technology Convergence
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• v.1 no.2
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• pp.01-09
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• 2022

Recently, safety issues in companies and public institutions are no longer a task that can be postponed, and when a major safety accident occurs, not only direct financial loss, but also indirect loss of social trust in the company and public institution is greatly increased. In particular, in the case of a fatal accident, the damage is even more serious. Accordingly, as companies and public institutions expand their investments in industrial safety education and prevention, open AI learning model creation technology that enables safety management services without being affected by user behavior in industrial sites where high-risk situations exist, edge terminals System development using inter-AI collaboration technology, cloud-edge terminal linkage technology, multi-modal risk situation determination technology, and AI model learning support technology is underway. In particular, with the development and spread of artificial intelligence technology, research to apply the technology to safety issues is becoming active. Therefore, in this paper, an open cloud platform design method that can support AI model learning for high-risk site safety management is presented.

• Health Policy and Management
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• v.32 no.4
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• pp.356-367
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• 2022

Background: The emergence of new infectious diseases threatens public health, increasing socioeconomic damage, and national risks. This study aimed to develop an evidence-based risk assessment tool to quickly respond to new infectious diseases. Methods: The risk elements were extracted by reviewing the risk assessment methods of the World Health Organization, United States, Europe, United Kingdom, and Germany, and the validity and priority of elements were determined through expert meetings and Delphi surveys. Then, the scale and level for each risk element were defined and a final score calculation method according to the risk evaluation result was derived. The developed risk assessment tool was verified using data at the time of domestic transmission of an emerging infectious disease. Results: In case of spread of actual infectious diseases, priority is determined based on the criticality of the elements in each area of transmissibility and severity, from which the weighted score of the risk assessment is derived. Then, the risk score for each element was calculated by multiplying the average value of the risk evaluation by its weight and the evaluation risk assessment score for the two areas was calculated. At last, the final score is plotted in a matrix where the x-axis indicates the transmissibility and the y-axis the severity and plotted on the coordinate plane for time series use. Conclusion: With respect to transmissibility and severity, this risk assessment method to respond to new and re-emerging infectious diseases enables rapid and evidence-based evaluation by quantitatively and qualitatively assessing various risk elements.

• Ocean and Polar Research
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• v.45 no.3
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• pp.173-183
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• 2023

The barren ground phenomenon in Korea began to occur and spread in the southern coast region and in Jeju Island in the 1980s, and since the 1990s, the damage has become serious in the east coast region as well. Korea has enacted the fisheries resource management act to manage such barren ground through the installation of sea forests among projects for the creation of fishery resources. Until now, projects related to the identification of the cause of barren ground have focused on the density of crustose coralline algae, sea urchins and seaweed, so the original cause of barren ground has not yet been identified. In order to manage barren ground, it is necessary to identify the cause of barren ground. To identify these causes, it is necessary to comprehensively consider i) studies on spatial characteristics such as rock mass distribution, slope and water depth, ii) studies on ecological and oceanographic characteristics such as water temperature, salinity, El Niño, and typhoons etc, iii) studies on organisms such as crustose coralline algae, macroalgae, and sea urchins, and iv) studies on coastal use such as living and industrial sewage inflow. Next, as with regard to legislative policy proposals , it is necessary to prepare self-management measures by the government, local governments, and fishermen as well as address management problems related to the use of sea forests by fishermen after their creation . In addition, when creating a sea forest, a management model for each resource management plan is required, and evaluation indicators and indexes that can diagnose the cause of barren ground and guidelines for barren ground measures should be developed.

• 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.

• IMMUNE NETWORK
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• v.22 no.6
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• pp.48.1-48.13
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• 2022

With the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, which are randomly mutated, the dominant strains in regions are changing globally. The development of preclinical animal models is imperative to validate vaccines and therapeutics against SARS-CoV-2 variants. The objective of this study was to develop a non-human primate (NHP) model for SARS-CoV-2 Delta variant infection. Cynomolgus macaques infected with Delta variants showed infectious viruses and viral RNA in the upper (nasal and throat) and lower respiratory (lung) tracts during the acute phase of infection. After 3 days of infection, lesions consistent with diffuse alveolar damage were observed in the lungs. For cellular immune responses, all macaques displayed transient lymphopenia and neutrophilia in the early stages of infection. SARS-CoV-2 Delta variant spike protein-specific IgM, IgG, and IgA levels were significantly increased in the plasma of these animals 14 days after infection. This new NHP Delta variant infection model can be used for comparative analysis of the difference in severity between SARS-CoV-2 variants of concern and may be useful in the efficacy evaluation of vaccines and universal therapeutic drugs for mutations.