• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.3
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• pp.346-354
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• 2023

Objectives: Chemical accidents cause extensive human and environmental damage. Therefore, it is important to prepare measures to prevent their recurrence and minimize future damage through accident investigation. To this end, it is necessary to identify the accident occurrence process and analyze the extent of damage. In this study, the development process and damage range of actual chemical leakage accidents were analyzed using CFD. Methods: For application to actual chemical leakage accidents using FLACS codes specialized for chemical dispersion simulation among CFD codes, release rate calculation and 3D geometry were created, and scenarios for simulation were derived. Results: The development process of the accident and the dispersion behavior of materials were analyzed considering the influencing factors at the time of the accident. In addition, to confirm the validity of the results, we compared the results of the actual damage impact investigation and the simulation analysis results. As a result, both showed similar damage impact ranges. Conclusions: The FLACS code allows the detailed analysis of the simulated dispersion process and concentration of substances similar to real ones. Therefore, it is judged that the analysis method using CFD simulation can be usefully applied as a chemical accident investigation technique.

• Restorative Dentistry and Endodontics
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• v.48 no.4
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• pp.41.1-41.17
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• 2023

Objectives: This scientometric and bibliometric analysis explored scientific publications related to hydraulic calcium silicate-based (HCSB) sealers used in endodontology, aiming to describe basic bibliometric indicators and analyze current research trends. Materials and Methods: A comprehensive search was conducted in Web of Science and Scopus using specific HCSB sealer and general endodontic-related terms. Basic research parameters were collected, including publication year, authorship, countries, institutions, journals, level of evidence, study design and topic of interest, title terms, author keywords, citation counts, and density. Results: In total, 498 articles published in 136 journals were retrieved for the period 2008-2023. Brazil was the leading country, and the universities of Bologna in Italy and Sao Paolo in Brazil were represented equally as leading institutions. The most frequently occurring keywords were "calcium silicate," "root canal sealer MTA-Fillapex," and "biocompatibility," while title terms such as "calcium," "sealers," "root," "canal," "silicate based," and "endodontic" occurred most often. According to the thematic map analysis, "solubility" appeared as a basic theme of concentrated research interest, and "single-cone technique" was identified as an emerging, inadequately developed theme. The co-occurrence analysis revealed 4 major clusters centered on sealers' biological and physicochemical properties, obturation techniques, retreatability, and adhesion. Conclusions: This analysis presents bibliographic features and outlines changing trends in HCSB sealer research. The research output is dominated by basic science articles scrutinizing the biological and specific physicochemical properties of commonly used HCSB sealers. Future research needs to be guided by studies with a high level of evidence that utilize innovative, sophisticated technologies.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.93-101
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• 2024

Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.

• Korea Trade Review
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• v.48 no.1
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• pp.55-81
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• 2023

The purpose of this study is to analyze the main issues and trends of Korean trade, and to draw implications for future research regarding trade rules. A total of 476 academic journal are analyzed using English keyword searched for 'Trade Rules' from 2000 to July 2022 in the Korean Journal Citation Index data base. The analysis methodology includes co-occurrence network and topic trend analysis which is a kind of text mining methods. The results shows that key words representing Korea's trade trend fall into four categories in which the number of research journals has rapidly increased, which are Topic 4 (Investment Treaty), Topic 7 (Trade Security), Topic 8 (China's Protectionism), and Topic 11 (Trade Settlement). The major background for these topics is the tension between the United States and China threatening the existing international trade system. A detailed study for China's protectionism, changes in trade security system, and new investment agreements, and changes in payment methods will be the challenges in near future.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.563-572
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• 2024

Image processing and computer vision technologies are becoming increasingly important in a variety of application fields that require techniques and tools for sophisticated image analysis. In particular, image segmentation is a technology that plays an important role in image analysis. In this study, in order to identify recent research trends on image segmentation techniques, we used the Web of Science(WoS) database to analyze the R&D topography based on the network structure of the author's keyword co-occurrence matrix. As a result, from 2015 to 2023, as a result of the analysis of the R&D map of research articles on image segmentation, R&D in this field is largely focused on four areas of research and development: (1) researches on collecting and preprocessing image data to build higher-performance image segmentation models, (2) the researches on image segmentation using statistics-based models or machine learning algorithms, (3) the researches on image segmentation for medical image analysis, and (4) deep learning-based image segmentation-related R&D. The scientometrics-based analysis performed in this study can not only map the trajectory of R&D related to image segmentation, but can also serve as a marker for future exploration in this dynamic field.

• Journal of Korean Society of Archives and Records Management
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• v.24 no.1
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• pp.89-109
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• 2024

The study analyzed the research trends of domestic and international record information services from 2003 to 2022. A total of 136 academic papers registered in the Korea Citation Index (KCI) and 74 from the Library, Information Science & Technology Abstracts (LISTA) were examined by quantitative and qualitative content analysis to understand the research status of 20 years from various angles, such as publication year, research type, researcher type, subject, and purpose. Frequency analysis, co-occurrence frequency analysis, centrality analysis, and topic modeling were performed by applying text mining techniques. Results showed that domestic papers demonstrated a research flow focused on specific institutions or records, and user-centered satisfaction surveys and content-centered studies were conducted. Moreover, foreign papers confirmed various evaluation-oriented and information provision studies, such as data, resources, and collections, along with the research trend focusing on the relationship between archivists and users. The management of information resources was identified as a common topic in both domestic and foreign papers, but it is possible to identify that domestic research focuses on maintaining the quality of domestic information resources, while foreign research focuses on the storage and retrieval of information.

• The Plant Pathology Journal
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• v.40 no.3
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• pp.310-321
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• 2024

Tomato yellow leaf curl virus (TYLCV) and tomato spotted wilt virus (TSWV) are well-known examples of the begomovirus and orthotospovirus genera, respectively. These viruses cause significant economic damage to tomato crops worldwide. Weeds play an important role in the ongoing presence and spread of several plant viruses, such as TYLCV and TSWV, and are recognized as reservoirs for these infections. This work applies a comprehensive approach, encompassing field surveys and molecular techniques, to acquire an in-depth understanding of the interactions between viruses and their weed hosts. A total of 60 tomato samples exhibiting typical symptoms of TYLCV and TSWV were collected from a tomato greenhouse farm in Nonsan, South Korea. In addition, 130 samples of 16 different weed species in the immediate surroundings of the greenhouse were collected for viral detection. PCR and reverse transcription-PCR methodologies and specific primers for TYLCV and TSWV were used, which showed that 15 tomato samples were coinfected by both viruses. Interestingly, both viruses were also detected in perennial weeds, such as Rumex crispus, which highlights their function as viral reservoirs. Our study provides significant insights into the co-occurrence of TYLCV and TSWV in weed reservoirs, and their subsequent transmission under tomato greenhouse conditions. This project builds long-term strategies for integrated pest management to prevent and manage simultaneous virus outbreaks, known as twindemics, in agricultural systems.

• Explosives and Blasting
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• v.42 no.2
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• pp.12-28
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• 2024

Explosion involving rapid energy diffusion are causing enormous human and economic damage. Due to the advancement of the industry, various and widespread explosion accidents are occurring worldwise, and to prevent such explosion accidents, accurate cause analysis should be the basis. Research analysis related to worldwise explosion accidents was carried out in a limited range for some accidents. By conducting bibliometric analysis of keywords on all the papers published in international journals, this study attempted to derive the overall research trend by period and the latest fields in which future researchers may be interested. As a result of the study of keywords, the number of papers was generally small and the number of overall key words was small from 2005 to 2014, but numerical simulation and artificial intelligence have been used for the analysis of explosion accident cases since 2015, and various studies such as lithium-ion battery and mixed gas, which are the latest research fields, are currently being actively conducted.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.97-101
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• 2024

In this paper, we present the implementation of proton beam irradiation test logic and test results for Xilinx's RFSoC FPGA. In addition to the FPGA function, RFSoC is a chip that integrates CPU, ADC, and DAC and is attracting attention in the defense and space industries aimed at reducing the size of the chip. In order to use these chips in a space environment, an analysis of radiation effects was required and radiation mitigation measures were required. Through the proton irradiation test, the logic to measure the radiation effect of RFSoC was designed. Logic for comparing values stored in memory with normal values was implemented, and protons were irradiated to RFSoC to measure SEU generated in the block memory area. To alleviate the occurrence of SEU in other areas, TMR and SEM were applied and designed. Through the test results, we intend to verify this test configuration and establish an environment in which logic design for satellites can be verified in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.13 no.1
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• pp.10-20
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• 2024

As the online commerce market continues to expand with an increase of diverse products and content, users find it challenging in navigating and in the selection process. Thereafter both platforms and shopping malls are actively working in conducting continuous research on recommendations system to select and present products that align with user preferences. Most existing recommendation studies have relied on user data which is relatively easy to obtain. However, these studies only use a single type of event and their reliance on time dependent data results in issues with reliability and complexity. To address these challenges, this paper proposes a recommendation system that analysis user preferences in consideration of the relationship between various types of event data. The proposed recommendation system analyzes the correlation of multiple events, extracts weights, learns the recommendation model, and provides recommendation services through it. Through extensive experiments the performance of our system was compared with the previously studied algorithms. The results confirmed an improvement in both complexity and performance.