• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.152-161
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• 2023

In general, large-capacity hydrogen storage vessels, typically in the form of vertical cylindrical vessels, are constructed using steel materials. These vessels are anchored to foundation slabs that are specially designed to suit the environmental conditions. This anchoring method involves pre-installed anchors on top of the concrete foundation slab. However, it's important to note that such a design can result in concentrated stresses at the anchoring points when external forces, such as seismic events, are at play. This may lead to potential structural damage due to anchor and concrete damage. For this reason, in this study, it selected an vertical hydrogen storage vessel based on site observations and created a 3D finite element model. Artificial seismic motions made following the procedures specified in ICC-ES AC 156, as well as domestic recorded earthquakes with a magnitude greater than 5.0, were applied to analyze the structural behavior and performance of the target structures. Conducting experiments on a structure built to actual scale would be ideal, but due to practical constraints, it proved challenging to execute. Therefore, it opted for an analytical approach to assess the safety of the target structure. Regarding the structural response characteristics, the acceleration induced by seismic motion was observed to amplify by approximately ten times compared to the input seismic motions. Additionally, there was a tendency for a decrease in amplification as the response acceleration was transmitted to the point where the centre of gravity is located. For the vulnerable components, specifically the sub-system (support columns and anchorages), the stress levels were found to satisfy the allowable stress criteria. However, the concrete's tensile strength exhibited only about a 5% margin of safety compared to the allowable stress. This indicates the need for mitigation strategies in addressing these concerns. Based on the research findings presented in this paper, it is anticipated that predictable load information for the design of storage vessels required for future shaking table tests will be provided.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.

• Korean Journal of Culture and Social Issue
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• v.9 no.spc
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• pp.107-122
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• 2003

The object of this study is to evaluate the prevailing physical and psychosocial conditions regarding occupational low back injury. This study consists of two parts. In the first part of the study, analytic biomechanical model and NIOSH guidelines are applied to evaluate risk levels of low back injury for automobile assembly jobs. Total of 246 workers are analysed. There are 20 jobs having greater back compressive forces than 300kg at L5/S1. Also, there are 44 jobs over Action Limit with respect to 1981 NIOSH guidelines. The relationship between psychosocial factors and low back injury was examined in the second part of the study. A battery of questionnaires concerning the psychosocial stress based on PWI (Psychosocial Well-being Index) and musculoskeletal pain symptoms at low back was completed by 246 workers at the same plant. Results showed that 207 out 246 workers experienced the symptoms and 27 workers were diagnosed as patients. Two groups(low stressed, high stressed) based on PWI score had no significant relationships with both symptoms and results of diagnosis. The relationships between physical work load and psychosocial stress were also analysed. Specifically, some postural factors(vertical deviation angle of forearm, horizontal deviation angle of upperarm, vertical deviation angle of thigh, etc) were highly correlated with psychosocial stress. The results illustrated that PWI scores were associated with some physical workloads. However, psychosocial stress levels couldn't be well related with the pain symptom as well as the actual incidence of low back injury since pain or discomfort regarding low back injury were more complex than that of other musculoskeletal disorders.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.339-350
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• 2024

Purpose: This study analyzes accessibility of 10 hydrogen charging stations in Seoul and identifies areas that were difficult to access. The purpose is to re-analyze accessibility by adding a new location in terms of equity and safety of location placement, and then draw implications by comparing the improvement effects. Method: By applying the location-allocation model and the service area model based on network analysis of the ArcGIS program, areas with weak access were identified. The location selection method applied the 'Minimize Facilities' method in consideration of the need for rapid arrival to insufficient hydrogen charging stations. The limit distance for arrival within a specific time was analyzed by applying the average vehicle traffic speed(23.1km/h, Seoul Open Data Square) in 2022 to three categories: 3,850m(10minutes), 5,775m(15minutes), 7,700m(20minutes). In order to minimize conflicts over the installation of hydrogen charging stations, special standards of the Ministry of Trade, Industry and Energy applied to derive candidate sites for additional installation of hydrogen charging stations among existing gas stations and LPG/CNG charging stations. Result: As a result of the analysis, it was confirmed that accessibility was significantly improved by installing 5 new hydrogen charging stations at relatively safe gas stations and LPG/CNG charging stations in areas where access to the existing 10 hydrogen charging stations is weak within 20 minutes. Nevertheless, it was found that there are still areas where access remains difficult. Conclusion: The location allocation model is used to identify areas where access to hydrogen charging stations is difficult and prioritize installation, decision-making to select locations for hydrogen charging stations based on scientific evidence can be supported.

• Journal of Wetlands Research
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• v.26 no.1
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• pp.62-71
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• 2024

To assess the ecological changes of Korean fir (Abies koreana E. H. Wilson) under climate change conditions, growth and physiological responses were analyzed over a 5-year period in a control group (outdoors) and in a treatment group where the temperature and CO2 levels were elevated to closely resemble RCP 4.5 conditions. The results showed an increasing trend in annual branch length of A.koreana in the climate change treatment group over time. While climate change conditions did not significantly impact the morphological differences of A.koreana leaves, they did influence the biomass of the leaves, suggesting that as climate change progresses, the productivity of A.koreana leaves may decline. On the other hand, the chlorophyll content in A.koreana under climate change conditions was higher in the climate change treatment group, whereas the photosynthesis rate, transpiration rate, water use efficiency and stomatal conductance was higher in the control group. This suggests that an environment with elevated temperature and CO2 could influence an increase in stomatal density, but having a negative impact on photosynthetic reactions. Further research on stomatal density under each environmental treatment will be required to confirm this hypothesis. Additionally, as this study only observed changes in leaf biomass, further empirical research should be considered to understand the changes in biomass of A.koreana under climate change conditions. In conclusion, the environmental adaptability of A.koreana is expected to weaken in the long term under elevated temperatures and CO2.

• The Korean Society of Law and Medicine
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• v.25 no.1
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• pp.87-115
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• 2024

In Korea, exposure to stress has been accompanied by mental pain in the process of achieving many growth along with rapid development, various social problems, and the frequency of emergency hospitalization is increasing.. In the case of mentally ill patients, "unwanted hospitalization" is a problem, and police and 119 paramedics try to suppress the body of mentally ill patients, and many problems are exposed This is because the constituent requirements of the provisions of emergency hospitalization under the Mental Health and Welfare Act do not reflect reality, and each institution has a different position on one mentally ill person, and emergency hospitalization does not proceed smoothly or leads to friction between related organizations, and the safety of the mentally ill or others is not secured. Emergency hospitalization is defined as "a person who finds a person who is presumed to be mentally ill and is at high risk of harming his or her health or safety or others," and if the situation is so urgent that he or she cannot afford time to go through the hospitalization procedure to decide on his or her own hospitalization, he or she can request emergency hospitalization with the consent of a doctor and a police officer. In this case, 119 paramedics are escorted to a psychiatric institution. This provision of emergency hospitalization poses many problems in the process of transferring to psychiatric institutions. If a police officer or 119 paramedics in charge of practice use "physical force" during the emergency hospitalization process, side effects will inevitably occur, and professional negligence can be a problem. Specifically, when exercising physical force, the minimum necessary physical restraint based on laws and regulations and proportional principles is required, and the lack of the duty of care of 119 paramedics or police officers under the laws and regulations will eventually be resolved by applying other laws and regulations. Accordingly, it will be an opportunity for mentally ill patients to be transferred to psychiatric institutions in a safe environment by changing the subject of emergency hospitalization provisions under the Mental Health Welfare Act, defining and prescribing the use of physical protection guards as the enforcement regulations of the Mental Health Act, setting the duty of care for 119 paramedics and police officers, and creating an environment for transportation so that mentally ill patients can be treated safely.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.215-235
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• 2024

As artificial intelligence (AI) technology is recognized as a key technology that will determine future national competitiveness, competition for AI technology and industry promotion policies in major countries is intensifying. This study aims to present implications for domestic policy making by analyzing the policies of major countries on the start-up of AI companies, which are the basis of the AI industry ecosystem. The top four countries and the EU for the number of new investment attraction companies in the 2023 AI Index announced by the HAI Research Institute at Stanford University in the United States were selected, The United States enacted the National AI Initiative Act (NAIIA) in 2021. Through this law, The US Government is promoting continued leadership in the United States in AI R&D, developing reliable AI systems in the public and private sectors, building an AI system ecosystem across society, and strengthening DB management and access to AI policies conducted by all federal agencies. In the 14th Five-Year (2021-2025) Plan and 2035 Long-term Goals held in 2021, China has specified AI as the first of the seven strategic high-tech technologies, and is developing policies aimed at becoming the No. 1 AI global powerhouse by 2030. The UK is investing in innovative R&D companies through the 'Future Fund Breakthrough' in 2021, and is expanding related investments by preparing national strategies to leap forward as AI leaders, such as the implementation plan of the national AI strategy in 2022. Israel is supporting technology investment in start-up companies centered on the Innovation Agency, and the Innovation Agency is leading mid- to long-term investments of 2 to 15 years and regulatory reforms for new technologies. The EU is strengthening its digital innovation hub network and creating the InvestEU (European Strategic Investment Fund) and AI investment fund to support the use of AI by SMEs. This study aims to contribute to analyzing the policies of major foreign countries in making AI company start-up policies and providing a basis for Korea's strategy search. The limitations of the study are the limitations of the countries to be analyzed and the failure to attempt comparative analysis of the policy environments of the countries under the same conditions.

• Research in Plant Disease
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• v.30 no.2
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• pp.131-138
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• 2024

The effects of five fungicides on the spore growth phase of Alternaria dauci, which causes carrot leaf blight, were tested using the spore viability assay (SVA) and agar dilution method (ADM). The average EC₅₀ values for chlorothalonil against seven isolates of A. dauci examined by SVA and ADM were 14.21 ㎍/ml and more than 100 ㎍/ml. Dithianon and folpet also had lower EC₅₀ values in SVA than in ADM, while iminoctadine trisalbesilate had lower EC₅₀ value in ADM. For fluazinam, the EC₅₀ values of SVA and ADM were 1.63 and 2.40 ㎍/ml, respectively. As EC₅₀ values of five fungicides according to the spore growth phase of A. dauci KACC 42997, the efficacy of each fungicide as chlorothalonil, dithianon, and folpet decreased when treated after spore germination rather than when treated with spores before germination. However, iminoctadine tris-albesilate was more effective when treated after spores germinated than when treated before treatment. The excellent effect of fluazinam on the pathogen was maintained until A. dauci KACC 42997 was cultured in potato dextrose broth for 6 hr and the germ tube grew beyond the size of the spore. However, when treated with iminoctadine tris-albesilate and fluazinam after culturing for 12 hr, as the EC₅₀ values of the two fungicides increased to 8.87 and 20.65 ㎍/ml, their efficacies decreased. The results of this study show that the treatment time of the fungicide should be determined by considering the effect of the fungicide on the spore growth phase of pathogens.

• Food Science and Preservation
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• v.30 no.6
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• pp.1095-1106
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• 2023

This study investigated the anti-oxidative and anti-inflammatory effects of Aster glehni (AG) extract in RAW 264.7 cells and Caenorhabditis elegans. The total polyphenol and flavonoid contents were higher in the ethanol extracts than in the hot water extracts. As a result of measuring the moisture contents (%) and extraction yields (%) of AG and drying A. glehni for processing (DAG), 70% ethanol, which has the highest percentage of extraction yield, was selected as the final solvent. DPPH radical scavenging activity showed higher antioxidant activity of ethanol extracts of DAG than AG. The cytotoxicity assay of the AG or DAG ethanol extracts was treated at different concentrations (25, 50, and 100 ㎍/mL), and cell viability rates were higher than 80% at all concentrations. The LPS-stimulated nitric oxide (NO) production in RAW 264.7 was significantly reduced at all concentrations of AG and DAG groups. As a result of measuring the gene expression of iNOS, which induces NO production, the AG or DAG group decreased by 33% and 32%, compared with the phosphate buffer saline (PBS) group. Under inflammatory stress conditions, the survival rate of C. elegans treated with AG or DAG ethanol extract with LPS showed concentration-dependent improvement in survival rate compared with the PBS group. Considering these results, AG could potentially be developed as an antioxidant and anti-inflammatory functional food material.

• The Korean Society of Law and Medicine
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• v.24 no.4
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• pp.67-101
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• 2023

The utilization of generative AI in the medical field is also being rapidly researched. Access to vast data sets reduces the time and energy spent in selecting information. However, as the effort put into content creation decreases, there is a greater likelihood of associated issues arising. For example, with generative AI, users must discern the accuracy of results themselves, as these AIs learn from data within a set period and generate outcomes. While the answers may appear plausible, their sources are often unclear, making it challenging to determine their veracity. Additionally, the possibility of presenting results from a biased or distorted perspective cannot be discounted at present on ethical grounds. Despite these concerns, the field of generative AI is continually advancing, with an increasing number of users leveraging it in various sectors, including biomedical and life sciences. This raises important legal considerations regarding who bears responsibility and to what extent for any damages caused by these high-performance AI algorithms. A general overview of issues with generative AI includes those discussed above, but another perspective arises from its fundamental nature as a large-scale language model ('LLM') AI. There is a civil law concern regarding "the memorization of training data within artificial neural networks and its subsequent reproduction". Medical data, by nature, often reflects personal characteristics of patients, potentially leading to issues such as the regeneration of personal information. The extensive application of generative AI in scenarios beyond traditional AI brings forth the possibility of legal challenges that cannot be ignored. Upon examining the technical characteristics of generative AI and focusing on legal issues, especially concerning the protection of personal information, it's evident that current laws regarding personal information protection, particularly in the context of health and medical data utilization, are inadequate. These laws provide processes for anonymizing and de-identification, specific personal information but fall short when generative AI is applied as software in medical devices. To address the functionalities of generative AI in clinical software, a reevaluation and adjustment of existing laws for the protection of personal information are imperative.