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An Analytical Study on the Seismic Behavior and Safety of Vertical Hydrogen Storage Vessels Under the Earthquakes (지진 시 수직형 수소 저장용기의 거동 특성 분석 및 안전성에 관한 해석적 연구)

  • Sang-Moon Lee;Young-Jun Bae;Woo-Young Jung
    • 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.

Effect of Live Commerce Characteristics on Purchase Intention : Focusing on the Parallel Multiple Mediating Effect of Trust and Flow (라이브 커머스 특성이 구매 의도에 미치는 영향 : 신뢰와 몰입의 이중매개 효과를 중심으로)

  • Kim, Sung-jong;Chung, Byoung-gyu
    • Journal of Venture Innovation
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    • v.5 no.1
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    • pp.59-73
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    • 2022
  • Untact marketing is being activated due to COVID-19. As a result, live commerce, an untact seller, is also active in the e-commerce market. Therefore, in this study, we tried to find out what factors influence consumers when they purchase through live commerce. In particular, since consumers' trust and flow in live commerce platforms and products is important, their mediating effects were analyzed. The research model was established by deriving common variables among the characteristics of live commerce based on previous studies. An online survey was conducted for empirical analysis. 200 users who made at least one purchase in live commerce were analyzed. The study results are as follows. Among the characteristics of live commerce, entertainment, economics, professionality were found to have a positive (+) effect on purchase intention. On the other hand, ease of use did not significantly affect purchase intention. The influence was shown in the order of entertainment, professionality and economics. The mediating effect of trust was found to play a mediating role in that entertainment, economics, and professionality affect purchase intention. On the other hand, a significant mediating effect was not tested between ease of use and purchase intention. As for the mediating effect of flow, it was found that flow plays a mediating role in that entertainment and economics affect purchase intention. On the other hand, the mediating effect of flow in terms of ease of use and economics affecting purchase intention was not tested. As for the multiple mediating effect of flow and trust, the mediating effect of flow was stronger than the mediating effect of trust when entertainment had an effect on purchase intention. In terms of professionality affecting purchase intention, the mediating effect of flow was also stronger than the mediating effect of trust. On the other hand, it was analyzed that only trust had a mediating effect when economics had an effect on purchase intention. The results of this study empirically tested that entertainment, which is a fun and interesting factor of live commerce content, is the most important factor when consumers use live commerce. In addition, various results were derived, such as cases where trust and flow act as mediators at the same time or not at all. Practical implications can be found in that it provided a clue about what to prioritize in order to reach consumers for live commerce platform.

Research on Making a Disaster Situation Management Intelligent Based on User Demand (사용자 수요 기반의 재난 상황관리 지능화에 관한 연구)

  • Seon-Hwa Choi;Jong-Yeong Son;Mi-Song Kim;Heewon Yoon;Shin-Hye Ryu;Sang Hoon Yoon
    • Korean Journal of Remote Sensing
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    • v.39 no.5_2
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    • pp.811-825
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    • 2023
  • In accordance with the government's stance of actively promoting intelligent administrative service policies through data utilization, in the disaster and safety management field, it also is proceeding with disaster and safety management policies utilizing data and constructing systems for responding efficiently to new and complex disasters and establishing scientific and systematic safety policies. However, it is difficult to quickly and accurately grasp the on-site situation in the event of a disaster, and there are still limitations in providing information necessary for situation judgment and response only by displaying vast data. This paper focuses on deriving specific needs to make disaster situation management work more intelligent and efficient by utilizing intelligent information technology. Through individual interviews with workers at the Central Disaster and Safety Status Control Center, we investigated the scope of disaster situation management work and the main functions and usability of the geographic information system (GIS)-based integrated situation management system by practitioners in this process. In addition, the data built in the system was reclassified according to purpose and characteristics to check the status of data in the GIS-based integrated situation management system. To derive needed to make disaster situation management more intelligent and efficient by utilizing intelligent information technology, 3 strategies were established to quickly and accurately identify on-site situations, make data-based situation judgments, and support efficient situation management tasks, and implementation tasks were defined and task priorities were determined based on the importance of implementation tasks through analytic hierarchy process (AHP) analysis. As a result, 24 implementation tasks were derived, and to make situation management efficient, it is analyzed that the use of intelligent information technology is necessary for collecting, analyzing, and managing video and sensor data and tasks that can take a lot of time of be prone to errors when performed by humans, that is, collecting situation-related data and reporting tasks. We have a conclusion that among situation management intelligence strategies, we can perform to develop technologies for strategies being high important score, that is, quickly and accurately identifying on-site situations and efficient situation management work support.

Efficient Deep Learning Approaches for Active Fire Detection Using Himawari-8 Geostationary Satellite Images (Himawari-8 정지궤도 위성 영상을 활용한 딥러닝 기반 산불 탐지의 효율적 방안 제시)

  • Sihyun Lee;Yoojin Kang;Taejun Sung;Jungho Im
    • 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.

Retrieval of Hourly Aerosol Optical Depth Using Top-of-Atmosphere Reflectance from GOCI-II and Machine Learning over South Korea (GOCI-II 대기상한 반사도와 기계학습을 이용한 남한 지역 시간별 에어로졸 광학 두께 산출)

  • Seyoung Yang;Hyunyoung Choi;Jungho Im
    • Korean Journal of Remote Sensing
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    • v.39 no.5_3
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    • pp.933-948
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    • 2023
  • Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R2=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.

Estimation of Fractional Urban Tree Canopy Cover through Machine Learning Using Optical Satellite Images (기계학습을 이용한 광학 위성 영상 기반의 도시 내 수목 피복률 추정)

  • Sejeong Bae ;Bokyung Son ;Taejun Sung ;Yeonsu Lee ;Jungho Im ;Yoojin Kang
    • Korean Journal of Remote Sensing
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    • v.39 no.5_3
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    • pp.1009-1029
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    • 2023
  • Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R2 of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R2 of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

Development of Strategies to Improve Water Quality of the Yeongsan River in Connection with Adaptation to Climate Change (기후변화의 적응과 연계한 영산강 수질개선대책 개발)

  • Yong Woon Lee;Won Mo Yang;Gwang Duck Song;Yong Uk Ryu;Hak Young Lee
    • Korean Journal of Ecology and Environment
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    • v.56 no.3
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    • pp.187-195
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    • 2023
  • Almost all of the water from agricultural dams located to the upper of the Yeongsan river is supplied as irrigation water for farmland and thus is not discharged to the main stream of the river. Also, most of the irrigation water does not return to the river after use, adding to the lack of flow in the main stream. As a result, the water quality and aquatic health of the river have become the poorest among the four major rivers in Korea. Therefore, in this study, several strategies for water quality improvement of the river were developed considering pollution reduction and flow rate increase, and their effect analysis was performed using a water quality model. The results of this study showed that the target water quality of the Yeongsan river could be achieved if flow increase strategies (FISs) are intensively pursued in parallel with pollution reduction. The reason is because the water quality of the river has been steadily improved through pollution reduction but this method is now nearing the limit. In addition, rainfall-related FISs such as dam construction and water distribution adjustment may be less effective or lost if a megadrought continues due to climate change and then rainfall does not occur for a long time. Therefore, in the future, if the application conditions for the FISs are similar, the seawater desalination facility, which is independent of rainfall, should be considered as the priority installation target among the FISs. The reason is that seawater desalination facilities can replace the water supply function of dams, which are difficult to newly build in Korea, and can be useful as a climate change adaptation facility by preventing water-related disasters in the event of a long-term megadrought.

Intergenerational analysis of family values among Korean mothers: With specific focus on values of children, socialization attitudes, and support of elderly parents (한국 세대별 어머니 집단의 가족관련 가치의식 비교: 자녀가치와 양육태도 및 부모부양을 중심으로)

  • Uichol Kim;Young-Shin Park;Yong-Eun Kwon
    • Korean Journal of Culture and Social Issue
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    • v.11 no.1
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    • pp.109-142
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    • 2005
  • This paper examines the changes in family values in Korea by examining values of children, socialization values, and social support of elderly parents with young and olders mothers. A total of 314 mothers of infants (young mothers) and 395 mothers of adolescents (older mothers) completed a questionnaire compiled by Schwarz, Chakkarath, Trommsdorff, Schwenk and Nauck(2001) comprising of values of children, cultural values, socialization values, interpersonal relationship, social support, stress, and life-satisfaction. In terms of values of children, the older mothers are more likely to emphasize social values, such as continuing the family line. Young mothers are more likely to emphasize psychological values, such as the pleasure of seeing a child grow. As for reasons for net wanting to have children, young mothers are more likely to point out personal constraints than older mothers, such as restriction of freedom. Second, older mothers are more likely than young mothers to express willingness to provide support for their children and even when their children become adults. Older mothers had a more lenient expectation of their children in terms developmental timetable and to expect support from their children when compared with young mothers. Young mothers are more likely to socialize their children with greater warmth and at the same time have higher child-rearing stress when compared to older mothers. Third, when compared with older mothers, young mothers are more likely to receive practical and emotional support from their parents. On the other hand, older mothers are more likely to provide greater practical and emotional support to their parents than the young mothers. Overall, compared to young mothers, older mothers are more likely to hold traditional and conservative values of children and socialization values. These contrasting values reflect the changes in family structure and social change that have been progressing rapidly in recent years.

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Weights for Evaluation items of Conformity index of Bird breeding sites on the West and South coasts of Korea (서·남해 연안성 조류번식지 적합성지수 평가항목 가중치 설정)

  • Kim, Chang-Hyeon;Kim, Won-Bin;Kim, Kyou-Sub;Lee, Chang-Hun
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.41 no.4
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    • pp.40-48
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    • 2023
  • This study is part of a foundational research effort aimed at developing a suitability index for breeding grounds related to avian activities along the domestic South and West coasts, including islands. Focus Group Interviews (FGI) and Analytic Hierarchy Process (AHP) analyses were conducted. The results are as follows. First, as a result of determining the value of the suitability of coastal bird breeding sites, the 'Natural Value(0.763)' was higher than the 'Artificial Value(0.237)'. Other artificial values were identified as sub-ranked except for 'Protected Areas' to ensure continuous integrity of breeding spaces. Second, as a result of re-establishing the 25 evaluation items classified in the two-time FGI as higher concepts, nine natural values and five artificial values were finally selected as a total of 14. Third, the results of the mid-classification evaluation of the importance of the suitability of coastal bird breeding sites were identified in the order of 'Ecological Value(0.392)', 'Topographic Value(0.251)', 'Passive Interference(0.124)', 'Geological Value(0.120)', and 'Active Interference(0.113)'. Fourth, the results of the priority of evaluation items of coastal bird breeding sites were in the order of 'Vegetation Distribution (0.187)', 'Area of Mudflats(0.118)', 'Presence or Absence of Mudflats(0.092)', 'Appearance of Natural Enemies(0.087)', 'Protected Areas(0.08)', 'Island Area (0.069)', 'Over-Breeding devastation(0.064)', 'Soil Composition Ratio(0.056)', 'Distance from Land(0.054)', 'Ocean farm area (0.045)', 'Cultivated land area(0.041)', 'Cultivation behavior(0.038)', 'Angle of the Surface(0.036)', and 'Land Use(0.033)'. It is judged that the weighting result value of the evaluation items derived in this study can be used for priority evaluation focusing on the coastal bird breeding area space. However, it seems that the correlation with the unique habitat suitability of bird individuals needs to be supplemented, and spatial analysis research incorporating species-specific characteristics will be left as a future task.

The Presence of Related Personnel Effects on the IPO of Special Listed Firms on KOSDAQ Market: Based on the Signal Effect of Third-party Social Recognition (관계인사 영입이 코스닥 기술특례기업 IPO성과에 미치는 영향: 제3자 사회적 인정의 신호 효과를 바탕으로)

  • Kiyong, Kim;Young-Hee, Ko
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.6
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    • pp.13-24
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    • 2022
  • The purpose of this study is to examine whether the existence of related personnel in KOSDAQ technology special listed firms has a signal effect on the market and affects performance when listed. The KOSDAQ technology special listing system is a system introduced to enable future growth by securing financing through corporate public offering based on the technology and marketability of technology-based startups and venture companies. As a result of analyzing 135 special technology companies listed from 2005 to 21 (excluding SPAC mergers and foreign companies) whether or not related personnel affect corporate value and listing period when they are listed, it was analyzed that the presence of related personnel did not significantly affect corporate value or listing period. The same was found in the results of the verification by reducing the scope to related personnel such as public officials and related agencies. However, under certain conditions, significant results were derived from the presence of related personnel on the listing of companies listed in special technology cases. It was found that the presence of related personnel and VC investment had a significant effect on corporate value, and in the case of bio-industry, there was a slight significant effect on the duration of listing. This study is significant in that it systematically analyzed the signal effect of the existence of related personnel for the first time for all 135 companies. In addition, as a result of the analysis, the results suggest that internalized efforts to secure technology and marketability are more important, such as parallel to VC investment, rather than simply recruiting related personnel.