• Journal of the Korean Geotechnical Society
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• v.39 no.10
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• pp.41-48
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• 2023

The presence of abnormalities in the subgrade of roads poses safety risks to users and results in significant maintenance costs. In this study, we aimed to experimentally evaluate the temperature distributions in abnormal areas of subgrade materials using infrared cameras and analyze the data with machine learning techniques. The experimental site was configured as a cubic shape measuring 50 cm in width, length, and depth, with abnormal areas designated for water and air. Concrete blocks covered the upper part of the site to simulate the pavement layer. Temperature distribution was monitored over 23 h, from 4 PM to 3 PM the following day, resulting in image data and numerical temperature values extracted from the middle of the abnormal area. The temperature difference between the maximum and minimum values measured 34.8℃ for water, 34.2℃ for air, and 28.6℃ for the original subgrade. To classify conditions in the measured images, we employed the image analysis method of a convolutional neural network (CNN), utilizing ResNet-101 and SqueezeNet networks. The classification accuracies of ResNet-101 for water, air, and the original subgrade were 70%, 50%, and 80%, respectively. SqueezeNet achieved classification accuracies of 60% for water, 30% for air, and 70% for the original subgrade. This study highlights the effectiveness of CNN algorithms in analyzing subgrade properties and predicting subsurface conditions.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.403-428
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• 2023

This study investigates the development path and intellectual structure of data literacy research, aiming to identify emerging topics in the field. A comprehensive search for data literacy-related articles on the Web of Science reveals that the field is primarily concentrated in Education & Educational Research and Information Science & Library Science, accounting for nearly 60% of the total. Citation network analysis, employing the PageRank algorithm, identifies key papers with high citation impact across various topics. To accurately trace the development path of data literacy research, an enhanced PageRank main path algorithm is developed, which overcomes the limitations of existing methods confined to the Education & Educational Research field. Keyword bibliographic coupling analysis is employed to unravel the intellectual structure of data literacy research. Utilizing the PNNC algorithm, the detailed structure and clusters of the derived keyword bibliographic coupling network are revealed, including two large clusters, one with two smaller clusters and the other with five smaller clusters. The growth index and mean publishing year of each keyword and cluster are measured to pinpoint emerging topics. The analysis highlights the emergence of critical data literacy for social justice in higher education amidst the ongoing pandemic and the rise of AI chatbots. The enhanced PageRank main path algorithm, developed in this study, demonstrates its effectiveness in identifying parallel research streams developing across different fields.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.713-723
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• 2023

Climate change is significantly affecting coastal areas, and its impacts are expected to intensify. Recent studies on climate change adaptation and risk assessment in coastal regions increasingly integrate the concepts of recovery resilience and vulnerability. The aim of this study is to develop a measurement model for coastal hazard recovery resilience in the context of climate change adaptation. Before constructing the measurement model, a comprehensive literature review was conducted on coastal hazard recovery resilience, establishing a conceptual framework that included operational definitions for vulnerability and recovery resilience, along with several feedback mechanisms. The measurement model for coastal hazard recovery resilience comprised four metrics (MRV, LRV, RTSPV, and ND) and a Coastal Resilience Index (CRI). The developed indices were applied to domestic coastal erosion cases, and regional analyses were performed based on the index grades. The results revealed that the four recovery resilience metrics provided insights into the diverse characteristics of coastal erosion recovery resilience at each location. Mapping the composite indices of coastal resilience indicated that the areas along the East Sea exhibited relatively lower coastal erosion recovery resilience than the West and South Sea regions. The developed recovery resilience measurement model can serve as a tool for discussions on post-adaptation strategies and is applicable for determining policy priorities among different vulnerable regional groups.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.893-901
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• 2023

The International Association Marine Aids to Navigation and Lighthouse Authorities (IALA) proposed guidelines for VTS manual operation in 2016 for safe and efficient operation of ship. The Korea Coast Guard (KCG) established and operated 19 VTS centers in ports and coastal waters across the country by 2022 based on the IALA VTS manual and VTS operator's education and training guidelines. In addition, IALA proposed the Inter-VTS Exchange Format (IVEF) Service recommendation (V-145), a standard for data exchange between VTS, in 2011 for efficient e-Navigation system services and safe and efficient VTS service support by VTS authorities. The IVEF service in a common framework for ship information exchange, and it presents seven basic IVEF service (BISs) models. VTS service providers can provide safer and more efficient VTS services by sharing VTS information on joint area using IVEF standards. Based on the BIS data, interaction, and interfacing models, this paper introduced the development of the cloud-based VTS integration services performed by the KCG and the results of the VTS integration platform test-bed for IVEF service implementation. In addition, the results of establishing a cloud VTS integrated platform test-bed for the implementation of IVEF service and implementing the main functions of IVEF service were presented.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.724-739
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• 2023

Located in the sea area between South Korea, North Korea, and China, the Yellow Sea plays an important role from a geopolitical perspective, and recently, as the use of marine space in the Yellow Sea is expanding, its social and economic values have been increasing further. In addition, owing to rapid climate changes, the need for joint response and cooperation between Korea and China is increasing in various fields, including changes in the marine environment and marine ecosystem and generation and movement of air pollutants. Accordingly, in this study, core topics were derived from research papers with the Yellow Sea as a keyword, and research trends to date were explored through author network analysis. As a specific research method, research papers related to the Yellow Sea published between 1984 and 2021 were extracted from the Web of Science database and were classified into four periods to derive core topics using topic modeling, a type of text mining. Furthermore, the influences of major research communities, researchers, and research institutes in the appropriate fields were identified through analyzing the author network, and their implications were presented. The analysis results indicated that the core topics of research papers on the Yellow Sea had changed over time, and differences existed in the influence (centrality) of key researchers. Finally, based on the results of this study, this study aims to identify research trends related to the Yellow Sea, major researchers, and research institutes and contribute to research cooperation between Korea and China regarding the Yellow Sea in the future.

• Informatization Policy
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• v.30 no.4
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• pp.3-39
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• 2023

With the growing importance of information/information system, information security is emphasized, and the significance of information security audit as a tool for maintaining the proper security level is increasing as well. The objectives of the study are to identify the overall research trends and to propose future research areas by analyzing domestic and overseas research in the area. To achieve the objectives, 103 research papers were analyzed based on both general and subject-related criteria. The following are the major research results : In terms of research approach, more empirical studies are needed; For subject "Auditor," studies to develop a framework for related variables (e.g., capability) are needed; For subject "Audit Activities/Procedures," future research should focus on the process/results of detailed audit activities; Future domestic research for "Audit Areas" should look for the new technology/industry/security areas covered by foreign studies; For "Audit Objective/Impact," studies to define the variables (e.g., performance and quality) systematically and comprehensively are needed; For "Audit Standard/Guidelines," research on model/guideline needs to be continued.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2023.04a
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• pp.27-27
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• 2023

최근 기후위기 등으로 인해 생물다양성 감소 우려가 높아지고 있으며, 식물유전자원 보존의 강화를 위해 수많은 국제협약이 체결되고 있다. 자국의 생물다양성을 보호하고, 전 세계의 기후위기 취약식물의 보존을 위해 대한민국 산림청은 세계 최초로 지하터널형 야생식물종자 영구저장시설인 '시드볼트(Seed Vault)'를 경상북도 봉화에 설립하였다. 시드볼트는 안전한 종자의 저장을 위해 온도 -20℃, 습도 RH 40% 이하를 유지하며, 환경 변화를 최소화하기 위해 매일 시설 점검을 진행하고 있다. 시드볼트의 미션은 '기후위기 대응 생물다양성 확보'이며, 전 세계 종자저장의 선도기관으로 2022년 12월 기준으로 5,424종 192,625점을 확보하였으며, 2030년까지 1만 종 30만 점을 목표로 하고 있다. 전 세계 식물 종의 보호를 위해 국제기구와 협력하고 있으나, 해외 종자의 저장이 더욱 강화되어야 하며, 향후 시드볼트 종자저장 네트워크 구축에 참고하기 위한 해외 사례를 조사하였다. 아시아에서는 중국이 다량의 식물종을 수집하고 있으나, 해당 자료에 대한 공개는 이루어지지 않고 있으며, 일본은 농업식량 식물자원 중심으로 종자를 보존하고 있으며, 태국, 대만, 싱가포르 및 몽골 및 중앙아시아 국가의 종자수집과 보존은 근래 확대되는 추세이다. FAO의 Plant Genetic Resources for Food And Agriculture 관련 수집 자료에 따르면, 아시아지역 25개 국가에서 984,019점의 식물유전자원을 보고하였다. 본 연구를 바탕으로 아시아지역의 종자보존 네트워크를 구축하여 해외 종자의 안전한 저장을 통해 아시아 야생식물자원 다양성 보전 가치를 통합하는 시설로 성장하고자 한다.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.91-98
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• 2023

Recently, according to development of artificial intelligence, a wide range of industry being automatic and optimized. Also we can find out some research of using supervised learning for deteceting defect of railway in domestic rail industry. However, there are structures other than rails on the track, and the fastener is a device that binds the rail to other structures, and periodic inspections are required to prevent safety accidents. In this paper, we present a method of reducing cost for labeling using semi-supervised and transfer model trained on rail fastener data. We use Resnet50 as the backbone network pretrained on ImageNet. At first we randomly take training data from unlabeled data and then labeled that data to train model. After predict unlabeled data by trained model, we adopted a method of adding the data with the highest probability for each class to the training data by a predetermined size. Futhermore, we also conducted some experiments to investigate the influence of the number of initially labeled data. As a result of the experiment, model reaches 92% accuracy which has a performance difference of around 5% compared to supervised learning. This is expected to improve the performance of the classifier by using relatively few labels without additional labeling processes through the proposed method.

• Journal of Venture Innovation
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• v.5 no.3
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• pp.1-17
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• 2022

Entrepreneurs recognize that their passion was an important factor in driving successful entrepreneurship. However, they were often unaware of the impact that third-party passions related to startups have on them. Therefore, in this study, it was verified whether the accelerator incubation program had an effective effect on portfolios. At this time, I tried to do an empirical analysis focusing on how the third-party accelerator entrepreneur passion affects the entrepreneurial performance of portfolios. To this end, a survey was conducted on representatives of portfolios across the country who completed the accelerator incubation program, and empirical testing was conducted based on 330 valid ones. As a result of empirical analysis, it was confirmed that mentoring and networking among accelerator incubation programs had a positive (+) effect on entrepreneurial performance of portfolios. On the other hand, education and seed investment in the accelerator program did not significantly affect the entrepreneurial performance of portfolios. On the other hand, it was tested that accelerator entrepreneur passion significantly moderated both the incubation program elements (education, mentoring, network, seed investment) and the entrepreneurial performance of portfolios. The results of this study are meaningful in that they reveal that the passion of accelerator entrepreneurs is an important lynchpin of incubation programs and the key to success in startups. In addition, this study suggests that it is important for startups to go one step further from seed investment and properly identify the accelerator entrepreneur and his passion, the key man of accelerators.

• Journal of Venture Innovation
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• v.6 no.4
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• pp.153-170
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• 2023

Generative AI services, including ChatGPT, were becoming increasingly active. This study aimed to empirically analyze the factors that promoted and hindered the diffusion of such services from a consumer perspective. Accordingly, a research model was developed based on the Value-based Adoption Model (VAM) framework, addressing both benefit and sacrifice factors. Benefits identified included usefulness and enjoyment, while sacrifices were security and hallucination. The study analyzed how these factors affected the intention to use generative AI services. A survey was conducted among college students for empirical analysis, and 200 valid responses were analyzed. The analysis utilized structural equation modeling with AMOS 24. The empirical results showed that usefulness and enjoyment had a significant positive impact on perceived value, while security and hallucination had a significant negative impact. The order of influence on perceived value was usefulness, hallucination, security, and then enjoyment. Perceived value had a significant positive impact on usage intention. Moreover, perceived value was found to mediate the relationship between usefulness, enjoyment, security, hallucination, and the intention to use generative AI services. These findings expanded the research horizon academically by validating the effectiveness of generative AI services based on existing models and demonstrated the continued importance of usefulness in a practical context.