• Tribology and Lubricants
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• v.39 no.6
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• pp.235-243
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• 2023

This paper presents the fabrication process of water-lubricated plastic bearings. Plastic bearings require good mechanical properties and tribological properties as well as elasticity and shock resistance, especially when lubricated in dirty water conditions. In this study, sleeve-type plastic bearings are produced by winding a prepreg sheet, which primary contains nitrile rubber (NBR)-modified epoxy, self-lubricating fillers, and various types of lattice-structured reinforcing fibers such as carbon, Aramid, and polyethylene terephthalate. A thermosetting epoxy is chemically modified with NBR to impart elasticity and low-friction characteristics in water conditions. Experimental investigations are conducted to examine the mechanical and tribological characteristics of the developed bearing materials, and the results are compared with the characteristics of a commercial plastic bearing (Thordon SXL), well known as a water-lubricated bearing. A Thordon bearing (mainly composed of polyurethane) exhibits an extremely low load-bearing capacity and is thus only suitable for medium loading (1~10MPa). The tribological characteristics of the test materials are evaluated through Falex block-on-ring (LFW-1) friction and wear tests. The results indicate that friction exhibited by the carbon-fiber-reinforced NBR-10wt.%-modified epoxy composite material, incorporated with the addition of 20wt.% UHMWPE and 6wt.% paraffin wax, is lower than that of the Thorden bearings, whereas its wear resistance surpass that of Thorden ones. Because of these features, the load carrying capacity of the fabricated composite (>10MPa) is higher than that of the Thorden bearings. These results confirm the applicability of water-lubricated plastic bearing materials developed in this study.

• Women's Health Nursing
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• v.29 no.4
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• pp.302-316
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• 2023

Purpose: This study aimed to develop and validate a structural model for the quality of life (QoL) among high-risk pregnant women, based on Roy's adaptation model. Methods: This cross-sectional study collected data from 333 first-time mothers diagnosed with a high-risk pregnancy in two obstetrics and gynecology clinics in Cheonan, Korea, or participating in an online community, between October 20, 2021 and February 20, 2022. Structured questionnaires measured QoL, contextual stimuli (uncertainty), coping (adaptive or maladaptive), and adaptation mode (fatigue, state anxiety, antenatal depression, maternal identity, and marital adjustment). Results: The mean age of the respondents was 35.29±3.72 years, ranging from 26 to 45 years. The most common high-risk pregnancy diagnosis was gestational diabetes (26.1%). followed by preterm labor (21.6%). QoL was higher than average (18.63±3.80). Above-moderate mean scores were obtained for all domains (psychological/baby, 19.03; socioeconomic, 19.00; relational/spouse-partner, 20.99; relational/family-friends, 19.18; and health and functioning, 16.18). The final model explained 51% of variance in QoL in high-risk pregnant women, with acceptable overall model fit. Adaptation mode (β=-.81, p=.034) and maladaptive coping (β=.46 p=.043) directly affected QoL, and uncertainty (β=-. 21, p=.004), adaptive coping (β=.36 p=.026), and maladaptive coping (β=-.56 p=.023) indirectly affected QoL. Conclusion: It is essential to develop nursing interventions aimed at enhancing appropriate coping strategies to improve QoL in high-risk pregnant women. By reinforcing adaptive coping strategies and mitigating maladaptive coping, these interventions can contribute to better maternal and fetal outcomes and improve the overall well-being of high-risk pregnant women.

• Journal of Integrative Natural Science
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• v.17 no.2
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• pp.53-58
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• 2024

This study explores the enhancement of mechanical properties in Polymethyl Methacrylate (PMMA) composites through the incorporation of Methyl Methacrylate (MMA) and Ethylene Glycol Dimethacrylate (EGDMA). Utilizing Digital Light Processing (DLP) technology, we conducted a series of experiments to analyze the impact of varying concentrations of MMA and EGDMA on PMMA. The results indicate that while MMA demonstrates non-linear and variable mechanical strength across different PMMA concentrations, EGDMA consistently improves mechanical strength as PMMA concentration increases. This consistent enhancement by EGDMA suggests a stable and predictable reinforcement effect, which is critical for applications requiring high mechanical strength. Our comparative analysis highlights that EGDMA is a more effective additive than MMA for optimizing the mechanical performance of PMMA composites. Specifically, EGDMA's ability to provide uniform reinforcement across various PMMA concentrations makes it ideal for high-strength applications. These findings are significant for material scientists and engineers focused on the design and development of advanced PMMA-based materials. In conclusion, this research underscores the importance of selecting appropriate additives to enhance the mechanical properties of PMMA composites. The superior performance of EGDMA in reinforcing PMMA suggests its potential for broader applications in fields such as automotive, construction, medical devices, and 3D printing. This study provides valuable insights that can guide future research and development in high-performance composite materials, paving the way for innovative applications and improved material efficiency.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.301-307
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• 2024

This study introduces a novel cascade fusion architecture aimed at enhancing thermal images across various scale conditions. The processing of thermal images at multiple scales has been challenging due to the limitations of existing methods that are designed for specific scales. To overcome these limitations, this paper proposes a unified framework that utilizes cascade feature fusion to effectively learn multi-scale representations. Confidence maps from different image scales are fused in a cascaded manner, enabling scale-invariant learning. The architecture comprises end-to-end trained convolutional neural networks to enhance image quality by reinforcing mutual scale dependencies. Experimental results indicate that the proposed technique outperforms existing methods in multi-scale thermal image enhancement. Performance evaluation results are provided, demonstrating consistent improvements in image quality metrics. The cascade fusion design facilitates robust generalization across scales and efficient learning of cross-scale representations.

• Advances in concrete construction
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• v.16 no.6
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• pp.291-302
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• 2023

As the first part of the body that strikes the ground during running, sports shoes are especially important for improving performance and reducing injuries. The use of new nanotechnology materials in the shoe's sole that can affect the movement angle of the foot and the ground reaction forces during running has not been reported yet. It is important to consider the material of the sole of the shoe since it determines the long-term performance of sports shoes, including their comfort while walking, running, and jumping. Running performance can be improved by polymer foam that provides good support with low energy dissipation (low energy dissipation). Running shoes have a midsole made of ethylene propylene copolymer (EPP) foam. The mechanical properties of EPP foam are, however, low. To improve the mechanical performance of EPP, conventional mineral fillers are commonly used, but these fillers sacrifice energy return. In this study, to improve the magnificence of physical education training with nanotechnology, carbon nanotubes (CNTs) derived from recycled plastics were prepared by catalytic chemical vapor deposition and used as nucleating and reinforcing agents. As a result of the results, the physical, mechanical, and dynamic response properties of EPP foam combined with CNT and zinc oxide nanoparticles were significantly improved. When CNT was added to the nanocomposites with a weight percentage of less than 0.5 wt%, the wear resistance, physical properties, dynamic stiffness, compressive strength, and rebound properties of EPP foams were significantly improved.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.51-59
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• 2024

This study examines the relationship between the release of the news and the individual stock returns. Investors utilize a variety of information sources to maximize stock returns when establishing investment strategies. News companies publish their articles based on stock recommendation reports of analysts, enhancing the reliability of the information. Defining release of a stock-recommendation news article as an event, we examine its economic impacts and propose a binary classification model that predicts the stock return 10 days after the event. XGBoost and LightGBM models are applied for the study with accuracy of 75%, 71% respectively. In addition, after categorizing the recommended stocks based on the listed market(KOSPI/KOSDAQ) and market capitalization(Big/Small), this study verifies difference in the accuracy of models across four sub-datasets. Finally, by conducting SHAP(Shapley Additive exPlanations) analysis, we identify the key variables in each model, reinforcing the interpretability of models.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.49-62
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• 2024

In this paper, a sustainable closed-loop supply chain (SCLSC) network model is proposed for domestic mobile phone industry. Economic, environmental and social factors are respectively considered for reinforcing the sustainability of the SCLSC network model. These three factors aim at minimizing total cost, minimizing total amount of CO₂ emission, and maximizing total social influence resulting from the establishment and operation of facilities at each stage of the SCLSC network model. Since they are used as each objective function in modeling, the SCLSC network model can be a multi-objective optimization problem. A mathematical formulation is used for representing the SCLSC network model and a hybrid meta-heuristic approach is proposed for efficiently solving it. In numerical experiment, the performance of the proposed hybrid meta-heuristic approach is compared with those of conventional meta-heuristic approaches using some scales of the SCLSC network model. Experimental results shows that the proposed hybrid meta-heuristic approach outperforms conventional meta-heuristic approaches.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.1
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• pp.55-70
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• 2024

The loss of biodiversity poses a significant threat not only to business sustainability and investment risk but also to societal well-being. Nature serves as a crucial driver for long-term business viability and economic prosperity. The Task Force on Nature-related Financial Disclosures (TNFD), established in September 2023, mandates that companies assess and disclose their impacts on nature. Despite this, many businesses lack a full understanding of their reliance on and impact upon natural capital and ecosystem services, leading to insufficient disclosures. This study evaluates the applicability of TNFD's assessment methodologies and indicators within a domestic context, highlighting the condition of nature and ecosystem services, and exploring potential synergies with national biodiversity policies. Our analysis suggests that TNFD necessitates a unique approach to the spatial and temporal data and methodologies traditionally employed in environmental impact assessments. This includes assessing the reciprocal influences of corporate activities on natural capital and ecosystem services via the LEAP framework. Moreover, in industries where the choice of specific indicators depends on unique sectoral traits, developing a standardized strategy for data and assessment indicators-adapted to local conditions-is crucial due to the variability in the availability of assessment tools and data. The proactive engagement of the private sector in ecosystem restoration projects is particularly promising for contributing towards national biodiversity objectives. Although TNFD is in its nascent phase, its global adoption by numerous companies signifies its potential impact. Successful implementation of TNFD is anticipated to deepen businesses' and financial institutions' understanding of natural capital and ecosystem services, thereby reinforcing their commitment to sustainable development.

• Journal of Distribution Science
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• v.22 no.4
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• pp.1-10
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• 2024

Purpose: This study is aimed to introduce the application of phantom approach with structural equation modelling method for online learning. By integrating these innovative methodologies, the research seeks to advance the understanding of how the phantom approach can effectively complement and augment structural equation modeling techniques. Research design, data and methodology: A theoretical framework of Technology Acceptance Model (TAM) was modified and updated. A questionnaire was developed and used to extract information from 189 instructors who used online learning as their primary medium. The Covariance Based Structural Equation Modelling (CBSEM) was applied to test the direct effects and the phantom approach is used to handle the 2 mediators in the model. Results:social influence, perceived usefulness, and perceived ease of use exerted discernible impacts on instructors' intentionsto engage in online learning. These findings illuminate the intricate dynamics influencing instructor behavior within the realm of online education, underscoring the significance of various factors in shaping their intentions. Conclusions: In additions, the perceived usefulness and perceived ease of use had mediated the effect of social influence and instructor intention using phantom approach. Therefore, one can have concluded that this modified model was also confirmed, thereby reinforcing distribution strategies to online learning and overall education presence.

• Steel and Composite Structures
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• v.50 no.6
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• pp.627-641
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• 2024

This paper presents an experimental and numerical study to investigate the behavior of the precast segmental concrete beams (PSCBs) utilizing high-strength concrete (HSC) connected in the zone of the maximum bending moment using steel extended endplate connections (EECs). The experimental study consisted of five beams as follows: The first beam was the control beam for comparison, which was an unconnected one-piece beam made of HSC. The other four other beams consisted of two identical pieces of precast concrete. An important point to be noted is that at the end of each piece, a steel plate was used with a thickness of 10 mm. Moreover, this steel plate was welded to the lower and upper reinforcing bars of the beam. Furthermore, the steel plate was made to connect the two pieces using the technique of EECs. Several variables were taken in these four beams, whether from the shape of the connection or enhancing the behavior of the connection using the post-tensioning technique. EECs without stiffeners were used for some of the tested beams. The behavior of these connections was improved using stiffeners and shear bolts. To get accurate results, a comparison was made between the behaviors of the five beams. Another important point to be noted is that Abaqus and SAP2000 programs were used to investigate the behavior of PSCBs and to ensure the accuracy of the modeling process which showed a good agreement with the experimental results. Additionally, the simplified modeling using SAP2000 was able to model the nonlinear behavior of PSCBs connected using steel EECs. It was found that the steel pre-tensioned bolted EECs, reinforced with steel stiffeners and shear anchors, could be used to connect the precast HSC segmental beams via the internal pre-stressing technique.