Wonjin Choi;Beom-Sik Moon;Chae-Uk Song;Young-Jin Kim
Journal of Navigation and Port Research
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v.48
no.3
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pp.164-170
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2024
The light buoy, a floating structure at sea, is prone to drifting due to external factors such as oceanic weather. This makes it imperative to monitor for any loss or displacement of buoys. In order to address this issue, the Ministry of Oceans and Fisheries aims to issue alerts for buoy displacement by analyzing historical buoy position data to detect patterns. However, periodic lifting inspections, which are conducted every two years, disrupt the buoy's location pattern. As a result, new patterns need to be analyzed after each inspection for location monitoring. In this study, buoy position data from various periods were analyzed using convex hull and distance-based clustering algorithms. In addition, the optimal data collection period was identified in order to accurately recognize buoy location patterns. The findings suggest that a nine-week data collection period established stable location patterns, explaining approximately 89.8% of the variance in location data. These results can improve the management of light buoys based on location patterns and aid in the effective monitoring and early detection of buoy displacement.
Journal of the Korean Regional Science Association
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v.40
no.2
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pp.91-106
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2024
Around the world, many countries experiencing the issue of shrinking cities are continually expanding high-speed rail networks to enhance regional accessibility and address imbalances. This study analyzed the effects of high-speed train operations on the age-specific population migration in South Korean municipalities from 2012 to 2019, taking into account the risk levels of shrinking cities. For this purpose, an analysis was conducted using age-specific net in-migration population as the dependent variable, employing the spatial panel autoregressive model. The research results indicated that the influence of high-speed rail on regional population inflow varies depending on the risk level of shrinking city. In other words, high-speed railway operations had positive effects on population inflow in the capital areas and some major cities, while explained population outflow in the other regions. High-speed railways particularly exerted a significant impact on the inflow of the young and middle-aged population, representing the working age, but this effect was also limited to regions with a low risk of shrinkage. The findings of this study emphasize the importance of considering planned population and industrial attraction when installing high-speed rail with the goal of achieving regional balanced development and mitigating shrinkage. The results of this study also suggest the need for subsequent research to explore factors that positively influence population structure and inflow based on the level of shrinkage risk in each region, as well as the introduction of new policies tailored to the specific situations of each local government.
Offshore wind power generation has significant advantages, including enhanced energy security and job creation. However, despite these benefits, South Korea has not fully utilized its potential in this sector. In contrast, offshore wind power industry development in Europe has been driven by government leadership. Drawing from this experience, South Korea also needs to relax regulations, strengthen necessary infrastructure, and enhance financial support systems to activate the offshore wind power industry. For this, sustained government leadership is absolutely essential. Without addressing the capacity issues in the power grid, we cannot expect offshore wind power generation to succeed. To address grid issues, we propose the enactment of a special law called the "Special Act on Grid Expansion." Considering KEPCO's financial situation, private investment should be encouraged for grid construction. The role of developers is crucial for the successful development and operation of offshore wind power. They manage risks throughout various stages, from site acquisition to construction and operation, which have a significant impact on the success or failure of projects. Since domestic developers currently lack experience in offshore wind power, a cooperative strategy that leverages the experience and technology of advanced countries is necessary. Energy issues should be recognized as important tasks beyond mere political ideologies, as they are crucial for the survival of the nation and its development. It is essential to form a public consensus and implement ways for residents to coexist with offshore wind power, along with the conservation of marine ecosystems and effective communication with stakeholders. Expansion of the offshore wind power industry requires support in various areas, including financial and tax incentives, technology research investment, and workforce development. In particular, achieving carbon neutrality by 2050 necessitates the activation of offshore wind power alongside efforts by major corporations to transition to renewable energy. South Korea, surrounded by the sea, holds significant offshore wind power potential, and it is our responsibility to harness it as a sustainable energy source for future generations. To activate the offshore wind power market, we need to provide financial and tax support, develop infrastructure and research, and foster a skilled workforce. As major corporations transition to renewable energy to achieve carbon neutrality by 2050, offshore wind power must play a significant role. It is our responsibility to fully utilize South Korea's potential and make offshore wind power a new driver of growth.
In the maritime shipping industry, imbalance between supply and demand has persistently increased, leading to the utilization of blank sailings by major shipping companies worldwide as a key means of flexibly adjusting vessel capacity in response to shipping market conditions. Traditionally, blank sailings have been frequently implemented around the Chinese New Year period. However, due to unique circumstances such as the global pandemic starting in 2020 and trade tensions between the United States and China, shipping companies have recently conducted larger-scale blank sailings compared to the past. As blank sailings directly impact freight transport delays, they can have negative repercussions from perspectives of both businesses and consumers. Therefore, this study employed Poisson regression models and negative binomial regression models to analyze the influence of maritime freight rate determinants on shipping companies' decisions regarding blank sailings, aiming to proactively address potential consequences. Results of the analysis indicated that, in Poisson regression analysis for 2M, significant variables included global container shipping volume, container vessel capacity, container ship scrapping volume, container ship newbuilding index, and OECD inflation. In negative binomial regression analysis, ocean alliance showed significance with global container shipping volume and container ship order volume, the alliance with container ship capacity and interest rates, non-alliance with international oil prices, global supply chain pressure index, container ship capacity, OECD inflation, and total alliance with container ship capacity and interest rates.
In the 1970s and 1980s, during the nascent phase of ginseng disease research, efforts concentrated on isolating and identifying pathogens. Subsequently, their physiological ecology and pathogenesis characteristics were scrutinized. This led to the establishment of a comprehensive control approach for safeguarding major aerial part diseases like Alternaria blight, anthracnose, and Phytophthora blight, along with underground part diseases such as Rhizoctonia seedling damping-off, Pythium seedling damping-off, and Sclerotinia white rot. In the 1980s, the sunshade was changed from traditional rice straw to polyethylene (PE) net. From 1987 to 1989, focused research aimed at enhancing disease control methods. Notably, the introduction of a four-layer woven P.E. light-shading net minimized rainwater leakage, curbing Alternaria blight occurrence. Since 1990, identification of the bacterial soft stem rot pathogen facilitated the establishment of a flower stem removal method to mitigate outbreaks. Concurrently, efforts were directed towards identifying root rot pathogens causing continuous crop failure, employing soil fumigation and filling methods for sustainable crop land use. In 2000, adapting to rapid climate changes became imperative, prompting modifications and supplements to control methods. New approaches were devised, including a crop protection agent method for Alternaria stem blight triggered by excessive rainfall during sprouting and a control method for gray mold disease. A comprehensive plan to enhance control methods for Rhizoctonia seedling damping-off and Rhizoctonia damping-off was also devised. Over the past 50 years, the initial emphasis was on understanding the causes and control of ginseng diseases, followed by refining established control methods. Drawing on these findings, future ginseng cultivation and disease control methods should be innovatively developed to proactively address evolving factors such as climate fluctuations, diminishing cultivation areas, escalating labor costs, and heightened consumer safety awareness.
RNA-sequencing (RNA-seq) is a technique used for providing global patterns of transcriptomes in samples. However, it can only provide the average gene expression across cells and does not address the heterogeneity within the samples. The advances in single-cell RNA sequencing (scRNA-seq) technology have revolutionized our understanding of heterogeneity and the dynamics of gene expression at the single-cell level. For example, scRNA-seq allows us to identify the cell types in complex tissues, which can provide information regarding the alteration of the cell population by perturbations, such as genetic modification. Since its initial introduction, scRNA-seq has rapidly become popular, leading to the development of a huge number of bioinformatic tools. However, the analysis of the big dataset generated from scRNA-seq requires a general understanding of the preprocessing of the dataset and a variety of analytical techniques. Here, we present an overview of the workflow involved in analyzing the scRNA-seq dataset. First, we describe the preprocessing of the dataset, including quality control, normalization, and dimensionality reduction. Then, we introduce the downstream analysis provided with the most commonly used computational packages. This review aims to provide a workflow guideline for new researchers interested in this field.
Despite the important roles of institutions and their collaboration in producing knowledge for innovation, the lack of accurate methods for identifying such knowledge-producing institutions has restricted empirical research on the role of institutions in innovation. This study explores methods to enhance the accuracy of identifying institutions involved in innovation process. To this end, we propose ways to improve accuracy in both aspects of information - data and algorithms - using bibliographic information in the digital health field. Specifically, in the data processing stage before applying algorithms, we address contextual inaccuracies of bibliographic information; in the algorithm application stage, we propose methods to improve the ambiguity of institution names (IND). When compared with the PKG dataset, which is publicly available datasets based on the same bibliographic information, our methods doubled the number of cases available for subsequent analysis. We also discovered that the contribution of Korean institutions in the digital health field is either underestimated or overestimated. The method presented in this study is expected to contribute to empirically researching the role of knowledge-producing institutions in innovation process and ecosystem.
Journal of the Korea institute for structural maintenance and inspection
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v.28
no.4
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pp.55-61
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2024
Recently, the number of aging concrete structures is steadily increasing. This is because many of these structures are reaching their expected lifespan. Such structures require accurate inspections and persistent maintenance. Otherwise, their original functions and performance may degrade, potentially leading to safety accidents. Therefore, research on objective inspection technologies using deep learning and computer vision is actively being conducted. High-resolution images can accurately observe not only micro cracks but also spalling and exposed rebar, and deep learning enables automated detection. High detection performance in deep learning is only guaranteed with diverse and numerous training datasets. However, surface damage to concrete is not commonly captured in images, resulting in a lack of training data. To overcome this limitation, this study proposed a method for generating concrete surface damage images, including cracks, spalling, and exposed rebar, using stable diffusion. This method synthesizes new damage images by paired text and image data. For this purpose, a training dataset of 678 images was secured, and fine-tuning was performed through low-rank adaptation. The quality of the generated images was compared according to three base models of stable diffusion. As a result, a method to synthesize the most diverse and high-quality concrete damage images was developed. This research is expected to address the issue of data scarcity and contribute to improving the accuracy of deep learning-based damage detection algorithms in the future.
Kyounghoon Kim;Yumi Kim;Sumin Baeck;Jeong Hyeun Ko
Journal of the Korean Society for information Management
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v.41
no.3
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pp.331-358
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2024
In the rapid digital transformation era, kiosks have become a common element in daily life. However, their widespread deployment has introduced new challenges for socially marginalized groups, including individuals with disabilities and the elderly. This study aims to evaluate the usability of kiosks for individuals with low vision and propose improvement strategies. The study was conducted with eight low-vision university students from A University in Gyeongsangbuk-do and four non-disabled university students from Daegu. Usability was assessed through experiments involving a self-service certificate issuance kiosk and a fast-food restaurant kiosk, using Jakob Nielsen's five usability evaluation criteria: learnability, efficiency, memorability, error prevention, and satisfaction. The results revealed that individuals with low vision faced significant difficulties with small text size, low contrast, no physical buttons, and lack of screen zoom functionality. To address these issues, the study recommends enhancements such as increasing text size and contrast, incorporating physical buttons, adding zoom functionality, ensuring consistent UI design, and providing auditory feedback. This study provides foundational data for enhancing information accessibility for individuals with low vision. It offers critical insights into kiosk design and policy recommendations, thereby contributing to the mitigation of the digital divide.
Ji Yun;Haitao Jiang;Zhou Jiani;Sunghoon Cho;Tae Soo Yun
Journal of the Institute of Convergence Signal Processing
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v.25
no.2
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pp.113-118
/
2024
Recently, advancements in artificial intelligence and computer graphics technology have led to the emergence of various virtual humans across multiple media such as movies, advertisements, broadcasts, games, and social networking services (SNS). In particular, in the advertising marketing sector centered around virtual influencers, virtual humans have already proven to be an important promotional tool for businesses in terms of time and cost efficiency. In Korea, the virtual influencer market is in its nascent stage, and both large corporations and startups are preparing to launch new services related to virtual influencers without clear boundaries. However, due to the lack of public disclosure of the development process, they face the situation of having to incur significant expenses. To address these requirements and challenges faced by businesses, this paper implements a photogrammetry-based facial capture system for creating realistic virtual humans and explores the use of these models and their application cases. The paper also examines an optimal workflow in terms of cost and quality through MetaHuman modeling based on Unreal Engine, which simplifies the complex CG work steps from facial capture to the actual animation process. Additionally, the paper introduces cases where virtual humans have been utilized in SNS marketing, such as on Instagram, and demonstrates the performance of the proposed workflow by comparing it with traditional CG work through an Unreal Engine-based workflow.
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