• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.230-237
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• 2022

It is essential that service life of reinforced concrete structures in economic and safety aspects should be secured. It is well-known that chloride attack is a typical deterioration mechanism in field concrete structures. To prevent serious accidents like collapse, many studies have been conducted to increase resistance of chloride ingress using concrete mixed with GGBS. The usage of GGBS concrete is nowadays mandatory. Since most concretes in the field are unsaturated, study regarding chloride absorption is necessary, but many studies have focused on the chloride diffusion phenomenon. Methods for evaluating chloride absorption are cost and improper in the field. It is necessary to develop a simple method for evaluating chloride absorption in practice. This study evaluated resistance of chloride ingress in GGBS concretes with impedance measurement and absorption test. From the results, it was confirmed that the contents of absorbed chloride were linearly correlated with the measured electrical resistivities (or conductivities) in the concrete. At the end of the test, the electrical conductivities were 250.8 S/m (w/b=0.4) and 303.1 S/m (w/b=0.6) for PC concretes, and 2.6 S/m (w/b=0.4) and 64.4 S/m (w/b=0.6) for GGBS concretes, respectively. Considering influencing factors for chloride absorption and impedance measurement, chloride ingress into concrete is mainly affected by pore structures due to replacement of GGBS. Especially, formations of pore structure are different with binder, thereby binders should be considered in building reinforced concrete structures exposed to chloride environments.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.175-181
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• 2022

The condition of infrastructure deteriorates as the service life increases. Since most infrastructure in South Korea were intensively built during the period of economic growth, the proportion of outdated infrastructure is rapidly increasing now. Aging of such infrastructure can lead to safety accidents and even human casualties. To prevent these issues in advance, periodic and accurate inspection is essential. For this reason, the need for research to detect various types of damage using computer vision and deep learning is increasingly required in the field of remotely controlled or autonomous inspection. To this end, this study proposed a neural network structure that can detect concrete damage by classifying it into three types. In particular, the proposed neural network can detect them more accurately through a hierarchical learning technique. This neural network was trained with 2,026 damage images and tested with 508 damage images. As a result, we completed an algorithm with average mean intersection over union of 67.04% and F1 score of 52.65%. It is expected that the proposed damage detection algorithm could apply to accurate facility condition diagnosis in the near future.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1004-1010
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• 2021

Ship-floating object accidents can lead not only to a delay in ship's operations, but also to large scale casualties. Hence, preventive measures are required to avoid them. This study analyzed the spatiotemporal aspects of such collisions based on the data on ship-floating object accidents in sea areas in the last five years, including the collisions in South Korea's territorial seas and exclusive economic zones. We also provide basic data for related research fields. To understand the distribution of the relative density of accidents involving floating objects, the sea area under analysis was visualized as a grid and a two-dimensional histogram was generated. A multinomial logistic regression model was used to analyze the effect of variables such as time of day and season on the collisions. The spatial analysis revealed that the collision density was highest for the areas extending from Geoje Island to Tongyeong, including Jinhae Bay, and that it was high near Jeongok Port in the West Sea and the northern part of Jeju Island. The temporal analysis revealed that the collisions occurred most frequently during the day (71.4%) and in autumn. Furthermore, the likelihood of collision with floating objects was much higher for professional fishing vessels, leisure vessels, and recreational fishing vessels than for cargo vessels during the day and in autumn. The results of this analysis can be used as primary data for the arrangement of Coast Guard vessels, rigid enforcement of regulations, removal of floating objects, and preparation of countermeasures involving preliminary removal of floating objects to prevent accidents by time and season.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.36 no.5
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• pp.445-458
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• 1991

The literatures on meteorological disasters of which reported in Korea and abroad were reviewed and discussed in oilseed crops for refer to stable production and quality improvement of the crops. From the reviews, it was clarified that much of the reported disasters are almost same kinds as the other crops like reported in soybean and rice. However much of the disasters reported in oilseed crops were unconfirmed on their injury mechanisms or damage rate on yield loss and quality deteriorate comparing to the reports on soybean or rice. Among the meteorological disasters reported in oilseed crops, the disaters on sesame and groundnut were the most frequent in the numbers of report and water-flooding damage, drought damage, lodging damage in the kinds of disasters. Such kinds of the above disasters were leading to 90% yield loss in the most serious situation. To reduce the damage of meteorological disasters, it was suggested that the variety improvement of which highly resistant, and vinyl-mulching culture would be also an way to reduce water -logging and drought damage in sesame and groundnut in cultural practice. Further, it was indicated that the emphasis must be put on the oilseed crops to investigate and clarify the damage mechanisms, and reducing method of meteorological disasters in breeding and cultural practice.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.861-872
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• 2022

The purpose of this study was to establish a complex disaster scenario that can comprehensively consider various disaster situations that may occur in the utility tunnel. Method: In order to comprehensively consider the correlation between disasters, a composite disaster scenario was derived from a combination of damage factors, respectively. A risk assessment was performed in order to derive the priorities of the scenarios. And based on the results, the priorities of complex disaster scenarios were set. Result: Based on the disaster cases in the utility tunnel, a plan was prepared for complex disaster scenarios centered on damage. A complex disaster scenario was specified using a semi-quantitative evaluation method for single and multiple disaster factors such as fire, flooding, and earthquake. Conclusion: The composite disaster scenario derived from this study can be used for the prevention and preparation of damage when the precursor symptoms of a disaster are detected. In addition, the results of this study are expected to be used as basic data for preparing strategic plans and preparing complex disaster response technologies to induce rapid response and recovery in case of emergency disasters.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.19-36
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• 2023

As advances in information and communication technology have made it easier for anyone to produce and disseminate information, a new problem has emerged: fake news, which is false information intentionally shared to mislead people. Initially spread mainly through text, fake news has gradually evolved and is now distributed in multimedia formats. Since its founding in 2005, YouTube has become the world's leading video platform and is used by most people worldwide. However, it has also become a primary source of fake news, causing social problems. Various researchers have been working on detecting fake news on YouTube. There are content-based and background information-based approaches to fake news detection. Still, content-based approaches are dominant when looking at conventional fake news research and YouTube fake news detection research. This study proposes a fake news detection method based on background information rather than content-based fake news detection. In detail, we suggest detecting fake news by utilizing related video information from YouTube. Specifically, the method detects fake news through CNN, a deep learning network, from the vectorized information obtained from related videos and the original video using Doc2vec, an embedding technique. The empirical analysis shows that the proposed method has better prediction performance than the existing content-based approach to detecting fake news on YouTube. The proposed method in this study contributes to making our society safer and more reliable by preventing the spread of fake news on YouTube, which is highly contagious.

• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.1-11
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• 2023

Smart factory environments and digital twin environments are established, and today's factories accumulate vast amounts of production data and are managed in real time as visualized results suitable for user convenience. Production simulation techniques are in the spotlight as a way to prevent delays in delivery and predict factory volatility in situations where production schedule planning becomes difficult due to the diversification of production products. With the development of the digital twin environment, new packages are developed and functions of existing packages are updated, making it difficult for users to make decisions on which packages to use to develop simulations. Therefore, in this study, the concept of Discrete Event Simulation (DES) performed based on discrete events is defined, and the characteristics of various simulation packages were compared and analyzed. To this end, studies that solved real problems using discrete event simulation software for 10 years were analyzed, and three types of software used by the majority were identified. In addition, each package was classified by simulation technique, type of industry, subject of simulation, country of use, etc., and analysis results on the characteristics and usage of DES software were provided. The results of this study provide a basis for selection to companies and users who have difficulty in selecting discrete event simulation package in the future, and it is judged that they will be used as basic data.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.91-117
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• 2022

The number of depressed patients in Korea and around the world is rapidly increasing every year. However, most of the mentally ill patients are not aware that they are suffering from the disease, so adequate treatment is not being performed. If depressive symptoms are neglected, it can lead to suicide, anxiety, and other psychological problems. Therefore, early detection and treatment of depression are very important in improving mental health. To improve this problem, this study presented a deep learning-based depression tendency model using Korean social media text. After collecting data from Naver KonwledgeiN, Naver Blog, Hidoc, and Twitter, DSM-5 major depressive disorder diagnosis criteria were used to classify and annotate classes according to the number of depressive symptoms. Afterwards, TF-IDF analysis and simultaneous word analysis were performed to examine the characteristics of each class of the corpus constructed. In addition, word embedding, dictionary-based sentiment analysis, and LDA topic modeling were performed to generate a depression tendency classification model using various text features. Through this, the embedded text, sentiment score, and topic number for each document were calculated and used as text features. As a result, it was confirmed that the highest accuracy rate of 83.28% was achieved when the depression tendency was classified based on the KorBERT algorithm by combining both the emotional score and the topic of the document with the embedded text. This study establishes a classification model for Korean depression trends with improved performance using various text features, and detects potential depressive patients early among Korean online community users, enabling rapid treatment and prevention, thereby enabling the mental health of Korean society. It is significant in that it can help in promotion.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.189-200
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• 2022

Ground subsidence on urban roads is a social issue that can lead to human and property damages. Therefore, it is crucial to detect underground cavities in advance and repair them. Underground cavity detection is mainly performed using ground penetrating radar (GPR) surveys. This process is time-consuming, as a massive amount of GPR data needs to be interpreted, and the results vary depending on the skills and subjectivity of experts. To address these problems, researchers have studied automation and quantification techniques for GPR data interpretation, and recent studies have focused on deep learning-based interpretation techniques. In this study, we described a hyperbolic event detection process based on deep learning for GPR data interpretation. To demonstrate this process, we implemented a series of algorithms introduced in the preexisting research step by step. First, a deep learning-based YOLOv3 object detection model was applied to automatically detect hyperbolic signals. Subsequently, only hyperbolic signals were extracted using the column-connection clustering (C3) algorithm. Finally, the horizontal locations of the underground cavities were determined using regression analysis. The hyperbolic event detection using the YOLOv3 object detection technique achieved 84% precision and a recall score of 92% based on AP50. The predicted horizontal locations of the four underground cavities were approximately 0.12 ~ 0.36 m away from their actual locations. Thus, we confirmed that the existing deep learning-based interpretation technique is reliable with regard to detecting the hyperbolic patterns indicating underground cavities.

• Korea Trade Review
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• v.42 no.2
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• pp.53-76
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• 2017

To solve the crisis of bill of lading, every effort has been made to introduce the electronic bill of lading and sea waybill on a global basis. In spite of these efforts, electronic bill of lading is not introduced practically so farm but sea waybill is used in western nations to cope with the crisis of bill of lading. But there is a practice that surrendered bill of lading is used insead of sea waybill in Korea, China and Japan to do so. The surrendered bill of lading faces the problem that it is not considered legally as bill of lading and the decisions rendered by each nation's courts are different according to the usages of surrendered bill of lading. So careful consideration must be made in regard to these decisions. The purpose of this paper is to avoid the disputes in advance in using the surrendered bill of lading by analyzing the precedents for the surrendered bill of lading and finding its notes. This paper analyzed the precedents regarding the surrendered bill of lading and found the notes as follows; Firstly, the surrendered bill of lading is not a kind of bill of lading but a practice that a consignee can take delivery of the cargo without loss of time at destination without redemption of original bill of lading. Secondly, the parties must take legal steps in using the surrendered bill of lading as the bill of lading acts cannot apply to the surrendered bill of lading. Thirdly, the parties should establish their practice in using the surrendered bill of lading. Fourthly, it is reasonable to use the sea waybill as a substitute for the surrendered bill of lading.