• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.163-171
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• 2024

Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.41-51
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• 2024

In this paper, we explore the enhancement of target detection accuracy in the guided weapon using deep learning object detection on infrared (IR) images. Due to the characteristics of IR images being influenced by factors such as time and temperature, it's crucial to ensure a consistent representation of object features in various environments when training the model. A simple way to address this is by emphasizing the features of target objects and reducing noise within the infrared images through appropriate pre-processing techniques. However, in previous studies, there has not been sufficient discussion on pre-processing methods in learning deep learning models based on infrared images. In this paper, we aim to investigate the impact of image pre-processing techniques on infrared image-based training for object detection. To achieve this, we analyze the pre-processing results on infrared images that utilized global or local information from the video and the image. In addition, in order to confirm the impact of images converted by each pre-processing technique on object detector training, we learn the YOLOX target detector for images processed by various pre-processing methods and analyze them. In particular, the results of the experiments using the CLAHE (Contrast Limited Adaptive Histogram Equalization) shows the highest detection accuracy with a mean average precision (mAP) of 81.9%.

• Clinical and Experimental Vaccine Research
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• v.12 no.3
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• pp.240-248
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• 2023

Purpose: We reported a survey-based study assessing the parental intention to vaccinate children of 5 to 7 years old against coronavirus disease 2019 (COVID-19). The aim of this study is to assess factors influencing the parental intention to vaccinate their children against COVID-19. Materials and Methods: This study adopted a cross-sectional design, held at the public health center of Senen district, Jakarta, Indonesia from November 1-30, 2022. The off-line questionnaires were distributed via the school administrator to all eligible parents. Factors associated with intention to vaccinate were analyzed with the regression logistic models. Results: Of the 435 parents in this study, 215 had already vaccinated their children against COVID-19 (49.4%), and the overall intention of the participants to vaccinate was 69.7%. Factors associated with intention to vaccinate the children against COVID-19 were parental employment status, parental COVID-19 vaccine status and concern of contracting COVID-19. Parents who are employed, had completed vaccines with COVID-19 booster vaccine, and had concern of their children contracting COVID-19 were more likely to vaccinate their children (odds ratio [OR], 2.10; 95% confidence interval [CI], 1.22-3.69; p=0.011; OR, 2.15; 95% CI, 1.21-3.83; p=0.013; OR, 2.40; 95% CI, 1.34-4.30; p=0.004, respectively). Concern on the vaccine's side effects was negatively associated with the willingness to vaccinate. Conclusion: This study showed that childhood COVID-19 vaccine only covered half of the population, with parental intentions for childhood COVID-19 vaccination being high, reaching almost two-thirds of the study participants. Factors influencing parental intentions were employment status, parental COVID-19 vaccine status, concerns about COVID-19 and concerns about vaccine side effects.

• Korean Journal of Psychosomatic Medicine
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• v.32 no.1
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• pp.24-33
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• 2024

Objectives : The purpose of this study was to investigate individual- and community-level factors on suicidal ideation and suicide attempt among Korean adults. Methods : This study was conducted on 225,965 adults collected through data from the 2021 Community Health Survey and the Korean Statistical Information Service (KOSIS). The general characteristics, suicidal behavior (e.g., suicidal ideation, and suicide attempts), and community-level characteristics of the study subjects were analyzed using frequency (%) and mean (standard deviation). The effects on individual- and community-level factors on suicidal ideation and suicide attempts was analyzed using multilevel logistic regression models. Results : The community-level factor associated with suicidal ideation was unmet health care (Odds Ratio [OR]=1.053, 95% CI=1.035-1.071), and the community-level factor associated with suicide attempt was the aging rate (OR=1.015, 95% CI=1.001-1.030). Regarding health-related variables, the individual-level factors associated with suicidal ideation were stress status (OR=9.388, 95% CI=8.629-10.213), depressive experience in the past year (OR=6.737, 95% CI=6.454-7.032), and the predominantly individual-level factors associated with suicide attempt were also stress status (OR=5.213, 95% CI=3.699-7.347), and depressive experience in the last one year (OR=13.433, 95% CI: 11.247-16.044). Conclusions : We confirmed individual-level and community-level factors influencing suicidal ideation and suicide attempt. Through these findings, we need to establish suicide prevention policies, considering managing individual-level factors such as stress and depression as well as community-level factors such as unmet health care.

• Smart Media Journal
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• v.12 no.11
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• pp.48-56
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• 2023

The technology of Three-dimensional human posture estimation is used in sports, motion recognition, and special effects of video media. Among various methods for this, multi-view 3D human pose estimation is essential for precise estimation even in complex real-world environments. But Existing models for multi-view 3D human posture estimation have the disadvantage of high order of time complexity as they use 3D feature maps. This paper proposes a method to extend an existing monocular viewpoint multi-frame model based on Transformer with lower time complexity to 3D human posture estimation for multi-viewpoints. To expand to multi-viewpoints our proposed method first generates an 8-dimensional joint coordinate that connects 2-dimensional joint coordinates for 17 joints at 4-vieiwpoints acquired using the 2-dimensional human posture detector, CPN(Cascaded Pyramid Network). This paper then converts them into 17×32 data with patch embedding, and enters the data into a transformer model, finally. Consequently, the MLP(Multi-Layer Perceptron) block that outputs the 3D-human posture simultaneously updates the 3D human posture estimation for 4-viewpoints at every iteration. Compared to Zheng[5]'s method the number of model parameters of the proposed method was 48.9%, MPJPE(Mean Per Joint Position Error) was reduced by 20.6 mm (43.8%) and the average learning time per epoch was more than 20 times faster.

• Steel and Composite Structures
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• v.50 no.3
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• pp.281-298
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• 2024

Stainless steel bolts (SSB) are increasingly utilized in bolted steel connections due to their good mechanical performance and excellent corrosion resistance. Fire accidents, which commonly occur in engineering scenarios, pose a significant threat to the safety of steel frames. The post-fire behavior of SSB has a significant influence on the structural integrity of steel frames, and neglecting the effect of temperature can lead to serious accidents in engineering. Therefore, it is important to evaluate the performance of SSB at elevated temperatures and their residual strength after a fire incident. To investigate the mechanical behavior of SSB after fire, 114 bolts with grades A4-70 and A4-80, manufactured from 316L austenitic stainless steel, were subjected to elevated temperatures ranging from 20℃ to 1200℃. Two different cooling methods commonly employed in engineering, namely cooling at ambient temperatures (air cooling) and cooling in water (water cooling), were used to cool the bolts. Tensile tests were performed to examine the influence of elevated temperatures and cooling methods on the mechanical behavior of SSB. The results indicate that the temperature does not significantly affect the Young's modulus and the ultimate strength of SSB. Up to 500℃, the yield strength increases with temperature, but this trend reverses when the temperature exceeds 500℃. In contrast, the ultimate strain shows the opposite trend. The strain hardening exponent is not significantly influenced by the temperature until it reaches 500℃. The cooling methods employed have an insignificant impact on the performance of SSB. When compared to high-strength bolts, 316L austenitic SSB demonstrate superior fire resistance. Design models for the post-fire mechanical behavior of 316L austenitic SSB, encompassing parameters such as the elasticity modulus, yield strength, ultimate strength, ultimate strain, and strain hardening exponent, are proposed, and a more precise stress-strain model is recommended to predict the mechanical behavior of 316L austenitic SSB after a fire incident.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.4
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• pp.306-313
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• 2023

Sepsis is a systemic inflammatory response, with manifestations in multiple organs by pathogenic infection. Currently, there are no promising therapeutic strategies. Signal transducer and activator of transcription 3 (STAT3) is a cell signaling transcription factor. Niclosamide is an anti-helminthic drug approved by the Food and Drug Administration (FDA) as a potential STAT3 inhibitor. C57BL/6 mice were treated with an intraperitoneal injection of lipopolysaccharide (LPS). Niclosamide was administered orally 2 hours after the LPS injection. This study found that Niclosamide improved the survival and lung injury of LPS-induced mice. Niclosamide decreased the levels of interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and interleukin-1β (IL-1β), aspartate aminotransferase (AST), alanine aminotransferase (ALT), and lactate dehydrogenase (LDH) in serum. The effects of Niclosamide on phosphoinositide 3-kinase (PI3K), AKT, nuclear factor-κB (NF-κB), and STAT3 signaling pathways were determined in the lung tissue by immunoblot analysis. Niclosamide reduced phosphorylation of PI3K, AKT, NF-κB, and STAT3 significantly. Furthermore, it reduced the phosphorylation of STAT3 by LPS stimulation in RAW 264.7 macrophages. Niclosamide also reduced the LPS-stimulated expression of proinflammatory mediators, including IL-6, TNF-α, and IL-1β. Niclosamide provides a new therapeutic strategy for murine sepsis models by suppressing the inflammatory response through STAT3 inhibition.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.4
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• pp.298-305
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• 2023

Burkitt's lymphoma is a distinct subtype of non-Hodgkin's lymphoma originating from B-cells that is notorious for its aggressive growth and association with immune system impairments, potentially resulting in rapid and fatal outcomes if not addressed promptly. Optimizing the use of Food and Drug Administration-approved medications, such as combining known safe drugs, can lead to time and cost savings. This method holds promise in accelerating the progress of novel treatments, ultimately facilitating swifter access for patients. This study explores the potential of a dual-targeted therapeutic strategy, combining the bruton tyrosine kinase-targeting drug Ibrutinib and the epidermal growth factor receptor/human epidermal growth factor receptor-2-targeting drug Lapatinib. Ramos and Daudi cell lines, well-established models of Burkitt's lymphoma, were used to examine the impact of this combination therapy. The combination of Ibrutinib and Lapatinib inhibited cell proliferation more than using each drug individually. A combination treatment induced apoptosis and caused cell cycle arrest at the S and G2/M phases. This approach is multifaceted in its benefits. It enhances the efficiency of the drug development timeline and maximizes the utility of currently available resources, ensuring a more streamlined and resource-effective research process.

• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.157-164
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• 2023

The estuary dam is a structure installed and operated in a closed state except when flood event occurs to prevent inland saltwater intrusion and secure freshwater supply. However, the closed state of dam leads to issues such as eutrophication, so it is necessary to examine the extent of saltwater intrusion resulting from the opening of sluice gates. Groundwater, due to its subsurface conditions and slow flow characteristics, is widely analyzed using numerical models. OpenGeoSys, an open-source software capable of simulating Thermal- Hydraulic- Mechanical- Chemical phenomena, was adopted for this study. Simulations were conducted assuming natural flow conditions without dam and operating considering busy farming season, mostly from March to September. Verification of the model through analytical solutions showed error of 3.7%, confirming that OpenGeoSys is capable of simulating saltwater intrusion for these cases. From results simulated for 10 years, considering for the busy farming season, resulted in about 46% reduction in saltwater intrusion length compared to natural flow conditions, approximately 74.36 m. It may be helpful to make choices to use groundwater as a water resource.

• Korean Journal of Radiology
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• v.24 no.3
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• pp.190-203
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• 2023

Objective: We aimed to assess and validate the radiologic and clinical factors that were associated with recurrence and survival after curative surgery for heterogeneous targetoid primary liver malignancies in patients with chronic liver disease and to develop scoring systems for risk stratification. Materials and Methods: This multicenter retrospective study included 197 consecutive patients with chronic liver disease who had a single targetoid primary liver malignancy (142 hepatocellular carcinomas, 37 cholangiocarcinomas, 17 combined hepatocellular carcinoma-cholangiocarcinomas, and one neuroendocrine carcinoma) identified on preoperative gadoxetic acid-enhanced MRI and subsequently surgically removed between 2010 and 2017. Of these, 120 patients constituted the development cohort, and 77 patients from separate institution served as an external validation cohort. Factors associated with recurrence-free survival (RFS) and overall survival (OS) were identified using a Cox proportional hazards analysis, and risk scores were developed. The discriminatory power of the risk scores in the external validation cohort was evaluated using the Harrell C-index. The Kaplan-Meier curves were used to estimate RFS and OS for the different risk-score groups. Results: In RFS model 1, which eliminated features exclusively accessible on the hepatobiliary phase (HBP), tumor size of 2-5 cm or > 5 cm, and thin-rim arterial phase hyperenhancement (APHE) were included. In RFS model 2, tumors with a size of > 5 cm, tumor in vein (TIV), and HBP hypointense nodules without APHE were included. The OS model included a tumor size of > 5 cm, thin-rim APHE, TIV, and tumor vascular involvement other than TIV. The risk scores of the models showed good discriminatory performance in the external validation set (C-index, 0.62-0.76). The scoring system categorized the patients into three risk groups: favorable, intermediate, and poor, each with a distinct survival outcome (all log-rank p < 0.05). Conclusion: Risk scores based on rim arterial enhancement pattern, tumor size, HBP findings, and radiologic vascular invasion status may help predict postoperative RFS and OS in patients with targetoid primary liver malignancies.