• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.265-272
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• 2019

In this paper, a vision-based deep learning algorithm and image processing method are proposed to detect bolt-loosening in steel connections. To achieve this objective, the following approaches are implemented. First, a bolt-loosening detection method that includes regional convolutional neural network(RCNN)-based deep learning algorithm and Hough line transform(HLT)-based image processing algorithm are designed. The RCNN-based deep learning algorithm is developed to identify and crop bolts in a connection image. The HLT-based image processing algorithm is designed to estimate the bolt angles from the cropped bolt images. Then, the proposed vision-based method is evaluated for verifying bolt-loosening detection in a lab-scale girder connection. The accuracy of the RCNN-based bolt detector and HLT-based bolt angle estimator are examined with respect to various perspective distortions.

• Journal of Communication Design
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• v.60
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• pp.402-412
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• 2017

Since the 1990s, the role of the government has been shifting towards governance. This new governance emphasizes government's role in establishing a cooperative system with private organizations through network structure and interaction. In the 1990s, Korean Government support for artists and exhibitions increased unprecedentedly. In the 2000s, support for the arts shifted in ways so as to integrate genres. Simultaneously, in order to strengthen the creative capacities of artists, support for new artists, multi-art and fusion arts have increased. From 2010, 'visual arts' business support was provided. In addition, 'visual arts' was supported by a joint planning project from 2013 Also, an overseas residence program has actively supported exhibitions through international exchanges. Since 2005, it has expanded to cooperation with India, Iran and Asian countries as well as with the Betani Studio in Germany. In addition local government supported for artists and the Biennale, residences, regional cooperative business through the local cultural foundation.

• Journal of Internet of Things and Convergence
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• v.7 no.2
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• pp.7-12
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• 2021

Wisdom Contents are created with experiences and ideas of multiple authors, and consumed in Internet based Social Network Services that are not subjected to regional restrictions. Existing copyright management systems are designed for the protection of professional authors' rights, and effective in domestic area. On the contrary, the blockchain protocol is subjected to the service and the block is added by the consensus of participating nodes. If the data is stored to the blockchain, it cannot be modified or deleted. In this paper, we propose the blockchain based undeniable multi-signature scheme for the protection of multiple authorship on Wizdom Contents. The proposed scheme is consisted of co-authors' common public key generation, multi-signature generation and verification protocols. In the undeniable signature scheme, the signature cannot be verified without help of the signer. The proposed scheme is best suited to the contents purchase protocol. All co-authors cannot deny the fairness of the automated profit distribution through the verification of multiple authorship on Wizdom Contents.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.307-314
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• 2022

Recently, researches using deep learning-based models are being actively conducted to replace statistical-based time series forecast techniques to predict electric power demand. The result of analyzing the researches shows that the performance of the LSTM-based prediction model is acceptable, but it is not sufficient for long-term regional-wide power demand prediction. In this paper, we propose a WaveNet deep learning model to predict electric power demand 24-hour-ahead with temperature data in order to achieve the prediction accuracy better than MAPE value of 2% which statistical-based time series forecast techniques can present. First of all, we illustrate a delated causal one-dimensional convolutional neural network architecture of WaveNet and the preprocessing mechanism of the input data of electric power demand and temperature. Second, we present the training process and walk forward validation with the modified WaveNet. The performance comparison results show that the prediction model with temperature data achieves MAPE value of 1.33%, which is better than MAPE Value (2.33%) of the same model without temperature data.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.103-113
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• 2022

As globalization progresses and localization takes place, interest in local culture is increasing. In line with this trend, the Cultural Heritage Administration has been promoting the Cultural Heritage Night Tour Project as a night-type cultural property tourism content since 2016. Cultural property nightlife, part of the regional regeneration project, creates new added value by converging and combining various historical and cultural-related contents centered on local cultural heritage. Although the "cultural nightlife" has been greatly activated, it is judged that changes are needed to continue. This is because fixed nightlife programs are positive in terms of establishing a nationwide network, but there is a limitation in that they cannot be standardized and expanded to various forms. Therefore, in this study, the meaning and limitations of nightlife programs were identified, and cognitive theory applicable to nightlife programs was considered. Through this process, it was confirmed that cognitive poetry's 'circular for dynamic semantic composition', 'surreal foreground', and 'adventures in time and space' can be applied to nightlife programs. As a result of combining cognitive poetry with nightlife programs, it was possible to present a strategy for implementing nightlife programs differentiated from existing nightlife programs.

• Safety and Health at Work
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• v.13 no.3
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• pp.336-342
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• 2022

Background: This study aims to identify the safety and health risk perceptions toward the coronavirus disease-2019 (COVID-19) pandemic based on gender in Korean university students who work and study during the pandemic. Methods: A nationwide convenient sampling method was implemented to eliminate any regional characteristics in 757 university students, including those who studied while working. The participants answered the online questionnaire for one week. The collected data were analyzed using the R version 3.4.1 program. Results: The results comparing the safety and health risk perceptions toward COVID-19 based on the gender of the subjects who work while studying, "I often use the Internet to obtain information on COVID-19 infection control" are females appeared to use the internet more often (t = -2.18, p = 0.031) than males. "Compared to pre-COVID-19, I am currently feeling safe after the outbreak" is females felt less safe (t = 3.43, p < 0.001). Although COVID-19 infection control awareness is high among Korean university students and officials, males reported higher scores over females in all the questions, which was statistically significant. Conclusion: There should be prioritized psychological measures for prevention against COVID-19 for vulnerable groups with high mental health risks. A network must be established to protect the mental health of such groups, and candidates who require intervention must be actively identified and supported. Therefore, there must be efforts to deliver accurate information based on scientific evidence of the infectious disease, and the actions should be supported through such active communication.

• Molecules and Cells
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• v.45 no.5
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• pp.306-316
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• 2022

Chronic stress contributes to the risk of developing depression; the habenula, a nucleus in epithalamus, is associated with many neuropsychiatric disorders. Using genome-wide gene expression analysis, we analyzed the transcriptome of the habenula in rats exposed to chronic restraint stress for 14 days. We identified 379 differentially expressed genes (DEGs) that were affected by chronic stress. These genes were enriched in neuroactive ligand-receptor interaction, the cAMP (cyclic adenosine monophosphate) signaling pathway, circadian entrainment, and synaptic signaling from the Kyoto Encyclopedia of Genes and Genomes pathway analysis and responded to corticosteroids, positive regulation of lipid transport, anterograde trans-synaptic signaling, and chemical synapse transmission from the Gene Ontology analysis. Based on protein-protein interaction network analysis of the DEGs, we identified neuroactive ligand-receptor interactions, circadian entrainment, and cholinergic synapse-related subclusters. Additionally, cell type and habenular regional expression of DEGs, evaluated using a recently published single-cell RNA sequencing study (GSE137478), strongly suggest that DEGs related to neuroactive ligand-receptor interaction and trans-synaptic signaling are highly enriched in medial habenular neurons. Taken together, our findings provide a valuable set of molecular targets that may play important roles in mediating the habenular response to stress and the onset of chronic stress-induced depressive behaviors.

• Journal of Trauma and Injury
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• v.35 no.2
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• pp.76-83
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• 2022

Purpose: Ventilator-associated pneumonia is the most common nosocomial infection in patients with mechanical ventilation. In 2013, the new concept of ventilator-associated events (VAEs) replaced the traditional concept of ventilator-associated pneumonia. We analyzed risk factors for VAE occurrence and in-hospital mortality in trauma patients who received mechanical ventilatory support. Methods: In this retrospective review, the study population comprised patients admitted to the Jeju Regional Trauma Center from January 2020 to January 2021. Data on demographics, injury characteristics, and clinical findings were collected from medical records. The subjects were categorized into VAE and no-VAE groups according to the Centers for Disease Control and Prevention/National Healthcare Safety Network VAE criteria. We identified risk factors for VAE occurrence and in-hospital mortality. Results: Among 491 trauma patients admitted to the trauma center, 73 patients who received ventilator care were analyzed. Patients with a chest Abbreviated Injury Scale (AIS) score ≥3 had a 4.7-fold higher VAE rate (odds ratio [OR], 4.73; 95% confidence interval [CI], 1.46-17.9), and those with a glomerular filtration rate (GFR) <75 mL/min/1.73 m² had 4.1-fold higher odds of VAE occurrence (OR, 4.15; 95% CI, 1.32-14.1) and a nearly 4.2-fold higher risk for in-hospital mortality (OR, 4.19; 95% CI, 1.30-14.3). The median VAE-free duration of patients with chest AIS ≥3 was significantly shorter than that of patients with chest AIS <3 (P=0.013). Conclusions: Trauma patients with chest AIS ≥3 or GFR <75 mL/min/1.73 m² on admission should be intensively monitored to detect at-risk patients for VAEs and modify the care plan accordingly. VAEs should be closely monitored to identify infections early and to achieve desirable results. We should also actively consider modalities to shorten mechanical ventilation in patients with chest AIS ≥3 to reduce VAE occurrence.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1927-1934
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• 2021

The AtoN are installed and operated on the sea in order to help the safe navigation of ships. With the development of maritime ICT, to monitor and control the condition of AtoN from land using multiplex communication network such as AtoN AIS, CDMA, and LTE. Currently, The information of AtoN is difficult to integrated manage because AtoN management systems has been independently developed and operatie according to the operating conditions of the Regional Office of Oceans and Fisheries. In addition, in preparation for the introduction for e-navigation and MASS, systematic and unified information of AtoN is required. In this paper, we study to design and develop standard software for AtoN management system based on the international standard for navigation information(S-201). Through this study, it will be possible to provide continuous AtoN information and effective AtoN management.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.1-10
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• 2021

This paper aimed to look at the awareness of foreign workers in social platforms by using text mining, one of the big data techniques and draw suggestions for foreign workers. To achieve this purpose, data collection was conducted with search keyword 'Foreign Worker' from Jan. 1, to Dec. 31, 2020, and frequency analysis, TF-IDF analysis, and degree centrality analysis and 100 parent keywords were drawn for comparison. Furthermore, Ucinet6.0 and Netdraw were used to analyze semantic networks, and through CONCOR analysis, data were clustered into the following eight groups: foreigner policy issue, regional community issue, business owner's perspective issue, employment issue, working environment issue, legal issue, immigration issue, and human rights issue. Based on such analyzed results, it identified national awareness of foreign workers and main issues and provided the basic data on policy proposals for foreign workers and related researches.