• Journal of the Korean Applied Science and Technology
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• v.40 no.6
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• pp.1213-1224
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• 2023

The purpose of this study was to analyze the mediating role of self-efficacy in the relationship between the behavioral routines of beauty service workers on service performance and work performance. The subjects of the study were 311 beauty consumers in Seoul and Gyeonggi, and data were collected and analyzed using a structured questionnaire. For data analysis, descriptive statistics, confirmatory factor analysis(CFA), correlation analysis, structural equation model analysis(SEM), and mediating effect analysis using bootstrapping techniques were conducted. The conclusions drawn through a series of research procedures are as follows. First, the behavioral routines of beauty service workers were found to have a statistically significant positive(+) effect on self-efficacy, service performance, and work performance. Second, the self-efficacy of beauty service workers was found to have a statistically significant positive (+) effect on service performance and work performance. Third, the partial mediating effect of self-efficacy was shown in the relationship between beauty service workers' behavioral routines, service performance, and work performance.

• Journal of Forest and Environmental Science
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• v.40 no.2
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• pp.99-110
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• 2024

According to the REDD+ program, it is necessary to monitor, quantify, and report forest conditions in protected land areas. The objectives of this work were to quantify the average monthly aerial net primary productivity (ANPP_MONTH) of semi-arid Chaco Forest at Copo National Park (CNP), Santiago del Estero, Argentina, during the period 2000-2023, as well as its spatial distribution and relationship, and its use efficiency (RUE) of average monthly rainfall (AMR). The ANPP_MONTH model accounted for 90% of the seasonal variability from October to May, the average seasonal ANPP_MONTH was 145 tons of dry matter per hectare (t dm/ha), being the maximum in January with 192 t dm/ha and the minimum in May with 91 t dm/ha. The surface area covered by ANPP_MONTH exhibited a consistent positive trend from October to May (t test=15.65, p<0.01). Strong and significant direct relationships were found between ANPP_MONTH and AMRs, linear models explaining 90% and 96% of the variability, respectively. The results obtained become reference values for assessing the capacity of the forest systems to stock carbon for global warming mitigation and for monitoring and controlling their response to extreme climatic adversities. The average ANPP_MONTH reduces uncertainty when defining the thresholds to monitor and quantify ANPP and forest area, thus facilitating the detection of negative changes in land use in CNP. Such results evidence the National Parks Administration's high effectiveness for the maintenance of protected area and for the high ANPP of the FCHS of CNP in the period 2000-2023.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.217-229
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• 2024

Determining lateral earth pressure coefficient (EPC) K is a classic problem in geotechnical engineering. It is a key parameter for estimating the stresses in backfilled openings. For backfilled openings with rigid and immobile walls, some suggested using the Jaky's at-rest earth pressure coefficient K₀ while other suggested taking the Rankine's active earth pressure coefficient K_a. A single value was proposed for the entire backfilled opening. To better understand the distributions of stresses and K in a backfilled opening, a series of laboratory tests have been conducted. The horizontal and vertical normal stresses at the center and near the wall of the opening were measured. The values of K at the center and near the wall were then calculated with the measured horizontal and vertical normal stresses. The results show that the values of K are close to K_a at the center and close to K₀ near the wall. Furthermore, the experimental results show that the horizontal stress is almost the same at the center and near the wall, indicating a uniform distribution from the center to the wall. It can be estimated by analytical solutions using either K_a or K₀. The vertical stress is higher near the center than near the wall. Its analytical estimation can only be done by using K_a at the center and K₀ near the wall. Finally, the test results were used to calibrate a numerical model of FLAC2D, which was then used to analyze the influence of column size on the stresses and K in the backfilled opening.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.303-316
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• 2024

Seismic records are composed of mainshock and a series of aftershocks which often result in the incremental damage to underground structures and bring great challenges to the rescue of post-disaster and the repair of post-earthquake. In this paper, the repetition method was used to construct the mainshock-aftershocks sequence which was used as the input ground motion for the analysis of dynamic time history. Based on the Daikai station, the two-dimensional finite element model of soil-station was established to explore the failure process of station under different seismic precautionary intensities, and the concept of incremental damage of station was introduced to quantitatively analyze the damage condition of structure under the action of mainshock and two aftershocks. An arc rubber bearing was proposed for the shock absorption. With the arc rubber bearing, the mode of the traditional column end connection was changed from "fixed connection" to "hinged joint", and the ductility of the structure was significantly improved. The results show that the damage condition of the subway station is closely related to the magnitude of the mainshock. When the magnitude of the mainshock is low, the incremental damage to the structure caused by the subsequent aftershocks is little. When the magnitude of the mainshock is high, the subsequent aftershocks will cause serious incremental damage to the structure, and may even lead to the collapse of the station. The arc rubber bearing can reduce the damage to the station. The results can offer a reference for the seismic design of subway stations under the action of mainshock-aftershocks.

• Ocean Systems Engineering
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• v.14 no.1
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• pp.85-99
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• 2024

Ocean surface currents have an essential role in the Earth's climate system and significantly impact the marine ecosystem, weather patterns, and human activities. However, predicting ocean surface currents remains challenging due to the complexity and variability of the oceanic processes involved. This review article provides an overview of the current research status, challenges, and opportunities in the prediction of ocean surface currents. We discuss the various observational and modelling approaches used to study ocean surface currents, including satellite remote sensing, in situ measurements, and numerical models. We also highlight the major challenges facing the prediction of ocean surface currents, such as data assimilation, model-observation integration, and the representation of sub-grid scale processes. In this article, we suggest that future research should focus on developing advanced modeling techniques, such as machine learning, and the integration of multiple observational platforms to improve the accuracy and skill of ocean surface current predictions. We also emphasize the need to address the limitations of observing instruments, such as delays in receiving data, versioning errors, missing data, and undocumented data processing techniques. Improving data availability and quality will be essential for enhancing the accuracy of predictions. The future research should focus on developing methods for effective bias correction, a series of data preprocessing procedures, and utilizing combined models and xAI models to incorporate data from various sources. Advancements in predicting ocean surface currents will benefit various applications such as maritime operations, climate studies, and ecosystem management.

• Journal of The Korean Institute of Defense Technology
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• v.5 no.1
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• pp.7-18
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• 2023

The military leader makes an operation plan to accomplish combat missions. The current doctrine for an operation planning requires the use of simple and clear procedures and methods that can be carried out with human effort under adverse conditions in the field. The work in the process of an operation planning can be said to be a series of decision-making, and the criteria for decision-making generally apply mission variables. However, detailed standards are not fixed as doctrine, but are creatively established and applied. However, for AI-based decision-making, it is necessary to formalize the criteria and the format used. This paper first aims to standardize various criteria and forms to present a method that can be used in a semi-automated assist system, and to seek a plan to artificialize it. To this end, mathematical models and decision-making methods established in the field of operations research were applied to improve efficiency.

• Imaging Science in Dentistry
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• v.54 no.3
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• pp.257-263
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• 2024

Purpose: The purpose of this study was to classify mandibular molar furcation involvement (FI) in periapical radiographs using a deep learning algorithm. Materials and Methods: Full mouth series taken at East Carolina University School of Dental Medicine from 2011-2023 were screened. Diagnostic-quality mandibular premolar and molar periapical radiographs with healthy or FI mandibular molars were included. The radiographs were cropped into individual molar images, annotated as "healthy" or "FI," and divided into training, validation, and testing datasets. The images were preprocessed by PyTorch transformations. ResNet-18, a convolutional neural network model, was refined using the PyTorch deep learning framework for the specific imaging classification task. CrossEntropyLoss and the AdamW optimizer were employed for loss function training and optimizing the learning rate, respectively. The images were loaded by PyTorch DataLoader for efficiency. The performance of ResNet-18 algorithm was evaluated with multiple metrics, including training and validation losses, confusion matrix, accuracy, sensitivity, specificity, the receiver operating characteristic (ROC) curve, and the area under the ROC curve. Results: After adequate training, ResNet-18 classified healthy vs. FI molars in the testing set with an accuracy of 96.47%, indicating its suitability for image classification. Conclusion: The deep learning algorithm developed in this study was shown to be promising for classifying mandibular molar FI. It could serve as a valuable supplemental tool for detecting and managing periodontal diseases.

• The Korean Journal of Physiology and Pharmacology
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• v.28 no.5
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• pp.479-491
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• 2024

Improving liver regeneration (LR) remains a medical issue, and there is currently a lack of safe and effective drugs for LR. Rhizoma Dioscoreae (SanYak, SY) is a traditional Chinese medicine. However, the underlying action mechanism of SY treatment for LR is yet to be fully elucidated. To explore the mechanism by which SY affects LR, we have conducted a series of methods for network pharmacological analysis, molecular docking, and in vivo experimental validation in mice. Overall, 9 compounds and 30 predicted target genes of SY were found to be associated with the therapeutic effects of LR. Compared with the model group, hematoxylin and eosin staining revealed that the mice with preoperative drug intervention possessed fewer postoperative hepatocyte bubbles and relatively regular morphology. Furthermore, the serum alanine transaminase and aspartate aminotransferase levels were reduced, immunohistochemistry revealed elevated proliferating cell nuclear antigen positivity rate, and Western blotting demonstrated that the phospho-protein kinase B (AKT)/AKT ratio was downregulated and that vascular endothelial growth factor A (VEGFA) expression levels were upregulated. This study explored dioscin, the main active ingredient of SY, and its potential therapeutic effects on LR. It repairs damaged liver following surgery and promotes liver cell proliferation. The action mechanism comprises reducing AKT phosphorylation levels and upregulating VEGFA expression levels. Thus, this study provides a new direction for further research on the mechanism of SY promoting LR.

• Journal of the Korean Applied Science and Technology
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• v.41 no.3
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• pp.599-612
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• 2024

The purpose of this study is to impact of the physical risk factors of beauty workers on job burnout, presenteeism, and mental health and further verify the mediating effect of job burnout. Data were collected using questionnaires from 308 beauty workers in Seoul and Gyeonggi. The collected data were subjected to descriptive statistics, normality tests, confirmatory factor analyses, correlation, and structural equation model analyses, and mediation effect analyses were conducted using bootstrapping. The conclusions drawn through a series of research procedures are as follows. First, The physical risk factors of beauty workers were found to have a statistically significant effect on job burnout, presenteeism, and mental health. Second, job burnout was found to have a partial mediating effect in the relationship between the physical risk factors and the presnteeism of beauty workers. The results of this study can be used as basic data to raise awareness of the seriousness of the physical risk factors of beauty industry workers and further improve the quality of life of beauty industry workers.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3571-3584
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• 2024

Reactor core transient calculation is very important for the reactor safety analysis, in which the kernel is neutron kinetics calculation by simulating the variation of neutron density or thermal power over time. Compared with the point kinetics method, the time-space neutron kinetics calculation can provide accurate variation of neutron density in both space and time domain. But it consumes a lot of resources. It is necessary to develop a surrogate model that can quickly obtain the temporal and spatial variation information of neutron density or power with acceptable calculation accuracy. This paper uses the time-varying characteristics of power to construct a time function, parameterizes the time-varying characteristics which contains the information about the spatial change of power. Thereby, the amount of targets to predict in the space domain is compressed. A surrogate method using the machine learning is proposed in this paper. In the construction of a neural network, the input is processed by a convolutional layer, followed by a fully connected layer or a deconvolution layer. For the problem of time sequence disturbance, a structure combining convolutional neural network and recurrent neural network is used. It is verified in the tests of a series of 1D, 2D and 3D reactor models. The predicted values obtained using the constructed neural network models in these tests are in good agreement with the reference values, showing the powerful potential of the surrogate models.