• Journal of the Korean Geotechnical Society
• /
• v.39 no.10
• /
• pp.41-48
• /
• 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
• /
• v.40 no.4
• /
• pp.403-428
• /
• 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
• /
• v.29 no.7
• /
• pp.724-739
• /
• 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.

• Proceedings of the Plant Resources Society of Korea Conference
• /
• 2023.04a
• /
• pp.27-27
• /
• 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
• /
• v.24 no.6
• /
• pp.91-98
• /
• 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
• /
• v.5 no.3
• /
• pp.1-17
• /
• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.5
• /
• pp.21-27
• /
• 2023

As a means of helping ships navigate safely, navigational aids in operation in the maritime envirionment require periodic management, and due to the nature of the environment, it is difficult to visually check the exact state. As a result, the smart navigation aid system, which improves route safety and operational efficiency, utillizes expertise including sensors, communications, and information technology, unlike general route markings. The communication environment of the smart navigation aid system, which aims to ensure the safety of the navigators operating the ship and the safety of the ship, uses a wireless communication network in accordance with the marine environment. The ship collects the information necessary for the maritime environment on the land and operates. In this process, there is a need to consider the wireless communication security guideline. Basically, based on IHO S-100 a standard for facilitating data exchange and SECOM, which provides an interface for safe communication. This paper research a security system for safe communication in a maritime environment. The security system for the basic interface based on the document was presented, and there were some vulnerabillties to data exchange due to the wireless communication characteristics of the maritime environment, and the user authetication part was added considering the vulnerability that unauthorized users can access the service.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.6
• /
• pp.169-179
• /
• 2023

The purpose of this study is to suggest the direction of secondary school career education in a lifelong learning society. In that direction, first, it is necessary to strengthen teacher capacity and develop professionalism. Second, career education programs need to be improved and diversified. Third, it is necessary to strengthen collaboration and communication with career education experts as a way to strengthen cooperation and connection outside the school. Fourth, it is necessary to support online career education through improvement of career information network. Fifth, there are policy support and institutional improvement plans. Sixth, it is necessary to expand the subject of career education to the entire life. To this end, career education in secondary school is designed to flexibly cope with changes, overcome crises and turn them into opportunities, and provide experiences to solve problems. Comprehensive support for individually customized career education from a lifelong perspective that manages the degree is needed. Second, it is necessary to expand field-oriented career and job experience to provide sufficient job-related experience and support mentoring by field experts. Third, it is necessary to establish a career education network where schools, education offices, and local communities work together. Fourth, retraining of career counseling teachers is also necessary to support the strengthening of career education capacity of all teachers.

• Journal of the Institute of Convergence Signal Processing
• /
• v.24 no.2
• /
• pp.103-111
• /
• 2023

Consensus, that aims to converge the states of agents to the same states through information exchanges between agents, has been widely studied to control the multi-agent systems. In real systems, the measurement variables of each agent may be different, the loss of information across communication may occur, and the different networks for each state may need to be constructed for safety. Moreover, the input saturation and the disturbances in the system may cause instability. Therefore, this paper studies the PID(Proportional-Integral-Derivative)-based consensus control to achieve the swarm behavior of the multi-agent systems considering the heterogeneous state information, the input saturations, and the disturbances. Specifically, we consider the multiple follower agents and the single leader agent modeled by the second-order systems, and investigate the conditions to achieve the consensus based on the stability of the error system. It is confirmed that the proposed algorithm can achieve the consensus if only the connectivity of the position graph is guaranteed. Moreover, by extending the consensus algorithm, we study the formation control problem for the multi-agent systems. Finally, the validity of the proposed algorithm was verified through the simulations.

• Journal of the Institute of Convergence Signal Processing
• /
• v.24 no.1
• /
• pp.42-50
• /
• 2023

The development of technology has achieved digital innovation throughout the media industry, including production techniques and editing technologies, and has brought diversity in the form of consumer viewing through the OTT service and streaming era. The convergence of big data and deep learning networks automatically generated text in format such as news articles, novels, and scripts, but there were insufficient studies that reflected the author's intention and generated story with contextually smooth. In this paper, we describe the flow of pictures in the storyboard with image caption generation techniques, and the automatic generation of story-tailored scenarios through language models. Image caption using CNN and Attention Mechanism, we generate sentences describing pictures on the storyboard, and input the generated sentences into the artificial intelligence natural language processing model KoGPT-2 in order to automatically generate scenarios that meet the planning intention. Through this paper, the author's intention and story customized scenarios are created in large quantities to alleviate the pain of content creation, and artificial intelligence participates in the overall process of digital content production to activate media intelligence.