• Smart Media Journal
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• v.12 no.1
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• pp.9-16
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• 2023

Recently, a convolutional neural network (CNN) based system is being developed to overcome the limitations of human resources in the apple quality classification of farmhouse. However, since convolutional neural networks receive only images of the same size, preprocessing such as sampling may be required, and in the case of oversampling, information loss of the original image such as image quality degradation and blurring occurs. In this paper, in order to minimize the above problem, to generate a image patch based graph of an original image and propose a random walk-based positional encoding method to apply the graph transformer model. The above method continuously learns the position embedding information of patches which don't have a positional information based on the random walk algorithm, and finds the optimal graph structure by aggregating useful node information through the self-attention technique of graph transformer model. Therefore, it is robust and shows good performance even in a new graph structure of random node order and an arbitrary graph structure according to the location of an object in an image. As a result, when experimented with 5 apple quality datasets, the learning accuracy was higher than other GNN models by a minimum of 1.3% to a maximum of 4.7%, and the number of parameters was 3.59M, which was about 15% less than the 23.52M of the ResNet18 model. Therefore, it shows fast reasoning speed according to the reduction of the amount of computation and proves the effect.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.679-686
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• 2006

Recently, the city railway in the Seoul Metropolitan Area (SMA) has offered a low quality of service as a passage time, because it was operated slowly. So, the people who live in modern society are not satisfied about passage time, therefore, this study tried to make that the subway in the SMA becomes a more functional and effective wide-area-transportation-network through an express train introduction's method which examined cases from abroad and current system. and then presented how express train could be applied to current system. In a case study, We used the An-San Line and Su-In Line as a examples and developed a schedule which can minimize the delaying time of subway by using Branch & Bound Algorithm. The train operational plan was loaded to consider a railroad siding, Obtained site, and the dispatch interval(three to ten minutes) for the express and local lines and finally, We presented an alternative operational plan which made by those factors.

• 한국노년학
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• v.39 no.1
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• pp.1-20
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• 2019

Recently, the Ministry of Health and Welfare has emphasized the necessity to build community care, and the interest of health care- long-term care-social welfare system continues. In order to examine the future vision of long-term care for elderly people, which can be a core system in establishing community models for elderly people in the future, we will implement aging in place as a national policy project. It is meaningful to analyze in depth the case of Japan's policy implementation through the amendment process of long-term care insurance system. The purpose of this study is to examine the concept definition, operating system, and major promotion process of the Integrated Care System in Japan and to suggest policy implications for the future Korea long-term care insurance system. As a result of reviewing the operation status and revision process of the long-term care insurance system for establishing the Integrated care system in Japan, it is necessary to clarify the basic principles and construction of community care system, diversification of residence type and upgrading work, establishment of linkage network of health care-long term care-social welfare, expansion of support for family and self-mind.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.445-471
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• 2023

Long-term safety over millennia is the top priority consideration in the construction of disposal sites. However, ensuring the mechanical stability of deep geological repositories for spent fuel, a.k.a. radwaste, disposal during construction and operation is also crucial for safe operation of the repository. Imposing restrictions or limitations on tunnel support and lining materials such as shotcrete, concrete, grouting, which might compromise the sealing performance of backfill and buffer materials which are essential elements for the long-term safety of disposal sites, presents a highly challenging task for rock engineers and tunnelling experts. In this study, as part of an extensive exploration to aid in the proper selection of disposal sites, the anticipation of constructing a deep geological repository at a depth of 500 meters in an unknown state has been carried out. Through a review of 2D and 3D numerical analyses, the study aimed to explore the range of properties that ensure stability. Preliminary findings identified the potential range of rock properties that secure the stability of central and disposal tunnels, while the stability of the vertical tunnel network was confirmed through 3D analysis, outlining fundamental rock conditions necessary for the construction of disposal sites.

• International Journal of High-Rise Buildings
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• v.12 no.3
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• pp.225-234
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• 2023

Even at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the real-time decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS).

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1143-1150
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• 2023

The global climate crisis and the implementation of low-carbon policies have led to a growing interest in renewable energy and a growing number of related industries. Among them, solar power is attracting attention as a representative eco-friendly energy that does not deplete and does not emit pollutants or greenhouse gases. As a result, the supplement of solar power facility is increasing all over the world. However, solar power is easily affected by the environment such as geography and weather, so accurate solar power forecast is important for stable operation and efficient management. However, it is very hard to predict the exact amount of solar power using statistical methods. In addition, the conventional prediction methods have focused on only short- or long-term prediction, which causes to take long time to obtain various prediction models with different prediction horizons. Therefore, this study utilizes a many-to-many structure of a recurrent neural network (RNN) to integrate short-term and long-term predictions of solar power generation. We compare various RNN-based very short- and long-term prediction methods for solar power in terms of MSE and R² values.

• Information Systems Review
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• v.23 no.1
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• pp.69-91
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• 2021

Credit Bureaus in Korea commonly use financial transaction information of the past and present time for calculating an individual's credit scores. Compared to other rating factors, the repayment history information accounts for a larger weights on credit scores. Accordingly, despite full redemption of overdue payments, late payment history is reflected negatively for the assessment of credit scores for certain period of the time. An individual with debt delinquency can be classified into two groups; (1) the individuals who have faithfully paid off theirs overdue debts(Normal Repayment), and (2) those who have not and as differences of creditworthiness between these two groups do exist, it needs to grant relatively higher credit scores to the former individuals with normal repayment. This study is designed to analyze the factors of normal repayment of Korean financial debt delinquents based on credit information of personal loan, overdue payments, redemption from Korea Credit Information Services. As a result of the analysis, the number of overdue and the type of personal loan and delinquency were identified as significant variables affecting normal repayment and among applied methodologies, neural network models suggested the highest classification accuracy. The findings of this study are expected to improve the performance of individual credit scoring model by identifying the factors affecting normal repayment of a financial debt delinquent.

• Journal of agricultural medicine and community health
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• v.49 no.2
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• pp.132-145
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• 2024

Objectives: This study compares cases of Dalgubeol Health Care Project, 301 Network Project, and 3 for 1 Project based on program logic models to derive measures for promoting integrated healthcare and welfare services centered around medical institutions. Methods: From January to December 2021, information on the implementation systems and performance of each institution was collected. Data sources included prior academic research, project reports, operational guidelines, official press releases, media articles, and written surveys from project managers. A program logic model analysis framework was applied, structuring the information based on four elements: situation, input, activity, and output. Results: All three projects aimed to address the fragmentation of health and welfare services and medical blind spots. Despite similar multidisciplinary team compositions, differences existed in specific fields, recruitment scale, and employment types. Variations in funding sources led to differences in community collaboration, support methods, and future directions. There were discrepancies in the number of beneficiaries and medical treatments, with different results observed when comparing the actual number of people to input manpower and project cost per beneficiary. Conclusions: To design an integrated health and welfare service provision system centered on medical institutions, securing a stable funding mechanism and establishing an appropriate target population and service delivery system are crucial. Additionally, installing a dedicated department within the medical institution to link activities across various sectors, rather than outsourcing, is necessary. Ensuring appropriate recruitment and stable employment systems is needed. A comprehensive provision system offering services from mild to severe cases through public-private cooperation is suggested.

• Information Systems Review
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• v.19 no.3
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• pp.23-45
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• 2017

The ROK military is making a great effort and investment in establishing network-centric warfare, a future battlefield concept, as a major step in the establishment of a basic plan for military innovation. In the military organization level, an advanced process is introduced to shorten the command control time of the military and the business process is improved to shorten the decision time. In the information system dimension, an efficient resource management is achieved by establishing an automated command control system and a resource management information system by using the battle management information system. However, despite these efforts, we must evaluate the present level of informatization in an objective manner and assess the current progress toward the future goal of the military by using objective indicators. In promoting informatization, we must systematically identify the correct areas of improvement and identify policy directions to supplement in the future. Therefore, by analyzing preliminary research, workshops, and expert discussions on the major informatization level evaluation models at home and abroad, this study develops an evaluation model and several indicators that systematically reflect the characteristics of military organizations. The developed informatization level evaluation model is verified by conducting a feasibility test for the troops of the operation class or higher. We expect that this model will be able to objectively diagnose the level of informatization of the ROK military by putting budget and resources into the right place at the right time and to rapidly improve the vulnerability of the information sector.

• IMMUNE NETWORK
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• v.22 no.3
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• pp.22.1-22.25
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• 2022

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndromecoronavirus-2 (SARS-CoV-2), has spread over the world causing a pandemic which is still ongoing since its emergence in late 2019. A great amount of effort has been devoted to understanding the pathogenesis of COVID-19 with the hope of developing better therapeutic strategies. Transcriptome analysis using technologies such as RNA sequencing became a commonly used approach in study of host immune responses to SARS-CoV-2. Although substantial amount of information can be gathered from transcriptome analysis, different analysis tools used in these studies may lead to conclusions that differ dramatically from each other. Here, we re-analyzed four RNA-sequencing datasets of COVID-19 samples including human bronchoalveolar lavage fluid, nasopharyngeal swabs, lung biopsy and hACE2 transgenic mice using the same standardized method. The results showed that common features of COVID-19 include upregulation of chemokines including CCL2, CXCL1, and CXCL10, inflammatory cytokine IL-1β and alarmin S100A8/S100A9, which are associated with dysregulated innate immunity marked by abundant neutrophil and mast cell accumulation. Downregulation of chemokine receptor genes that are associated with impaired adaptive immunity such as lymphopenia is another common feather of COVID-19 observed. In addition, a few interferon-stimulated genes but no type I IFN genes were identified to be enriched in COVID-19 samples compared to their respective control in these datasets. These features are in line with results from single-cell RNA sequencing studies in the field. Therefore, our re-analysis of the RNA-seq datasets revealed common features of dysregulated immune responses to SARS-CoV-2 and shed light to the pathogenesis of COVID-19.