• The Journal of Korean Academy of Sensory Integration
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• v.21 no.3
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• pp.1-12
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• 2023

Objective : The purpose of this study was to compare the effects of the sensory processing characteristics of parents of developmentally delayed children and parents of typically developed children on parenting stress. Methods : From July to August 2022, 61 parents of children with developmental delays and 64 parents of children with typical development who used occupational therapy services at pediatric clinics and child development centers were evaluated for parenting stress and sensory profiles. Results : In a multiple regression analysis on the effect of sensory processing characteristics on the total score of parenting stress, tactile processing (β = 0.353, p = 0.001), gender (β = 0.438, p = 0.000), and monthly income (β = -0.261, p = 0.014) significantly affected the parenting stress of the parents of children with developmental delay. In parents of typically developing children, tactile processing (β = 0.376, p = 0.002) and gender (β = -0.264, p = 0.024) were found to have a significant effect on parenting stress. Conclusion : Parental gender and tactile processing characteristics of developmentally delayed and typically developing children are significant influencing factors for parenting stress.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.159-166
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• 2024

The purpose of this study was investigate the effect of self-efficacy, self-directedness and self-leadership on reslience in nursing students and to provide the basic data of to enhance resilience. Data were collected from 199 nursing students in B city. Data analysis was analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and multiple regression analysis using the SPSS 22.0 program. The degree of self-efficacy of the subjects was 3.63±0.52. Resilience of the subjects was positively correlated with self-efficacy (r=.677, p<.001), self-directedness (r=.573, p<.001), and self-leadership (r=.654, p<.001). Self-leadership of the subjects showed a positive correlation with self-efficacy (r=.517, p<.001), self-directedness (r=.665, p<.001). Self-directedness of the subjects showed a positive correlation with self-efficacy (r=.491, p<.001). The factors influencing the subject's resilience were identified as self-efficacy (β=.435, p<.001) and self-directedness (β=.133, p=.036), self-efficacy (β=.341, p<.001), and the explanatory power was 57.5%. Therefore, in order to improve nursing students' resilience, it is necessary to consider self-efficacy, self-directedness and self-leadership.

• Journal of Navigation and Port Research
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• v.48 no.1
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• pp.62-77
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• 2024

In the maritime shipping industry, imbalance between supply and demand has persistently increased, leading to the utilization of blank sailings by major shipping companies worldwide as a key means of flexibly adjusting vessel capacity in response to shipping market conditions. Traditionally, blank sailings have been frequently implemented around the Chinese New Year period. However, due to unique circumstances such as the global pandemic starting in 2020 and trade tensions between the United States and China, shipping companies have recently conducted larger-scale blank sailings compared to the past. As blank sailings directly impact freight transport delays, they can have negative repercussions from perspectives of both businesses and consumers. Therefore, this study employed Poisson regression models and negative binomial regression models to analyze the influence of maritime freight rate determinants on shipping companies' decisions regarding blank sailings, aiming to proactively address potential consequences. Results of the analysis indicated that, in Poisson regression analysis for 2M, significant variables included global container shipping volume, container vessel capacity, container ship scrapping volume, container ship newbuilding index, and OECD inflation. In negative binomial regression analysis, ocean alliance showed significance with global container shipping volume and container ship order volume, the alliance with container ship capacity and interest rates, non-alliance with international oil prices, global supply chain pressure index, container ship capacity, OECD inflation, and total alliance with container ship capacity and interest rates.

• Tunnel and Underground Space
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• v.34 no.1
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• pp.15-27
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• 2024

In this case study, detailed survey of the Excavation Damaged Zone (EDZ) evaluation for the deep geological repository for high level nuclear waste was conducted. Oversea and Domestic case studies were compiled and investigated. EDZ is considered a crucial factor in the performance assessment of spent fuel disposal, leading to numerous studies worldwide aiming to understand the characteristics of the EDZ and quantitatively assessment of its extent through field and laboratory tests at Underground Research Laboratory (URL) sites. To enhance the understanding of EDZ, this study begins with defining and exploring the history of EDZ, compiling factors influencing EDZ, and summarizing the impacts caused by EDZ. Subsequently, an analysis of EDZ and rock properties is performed, followed by presenting generalized outcomes, limitations drawn from previous research, and proposing future research directions.

• Steel and Composite Structures
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• v.50 no.6
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• pp.705-720
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• 2024

Analyzing the collapse behavior of thin-walled steel structures holds significant importance in ensuring their safety and longevity. Geometric imperfections present on the surface of metal materials can diminish both the durability and mechanical integrity of steel shells. These imperfections, encompassing local geometric irregularities and deformations such as holes, cavities, notches, and cracks localized in specific regions of the shell surface, play a pivotal role in the assessment. They can induce stress concentration within the structure, thereby influencing its susceptibility to buckling. The intricate relationship between the buckling behavior of these structures and such imperfections is multifaceted, contingent upon a variety of factors. The buckling analysis of thin-walled steel shell structures, similar to other steel structures, commonly involves the determination of crucial material properties, including elastic modulus, shear modulus, tensile strength, and fracture toughness. An established method involves the emulation of distributed geometric imperfections, utilizing real test specimen data as a basis. This approach allows for the accurate representation and assessment of the diversity and distribution of imperfections encountered in real-world scenarios. Utilizing defect data obtained from actual test samples enhances the model's realism and applicability. The sizes and configurations of these defects are employed as inputs in the modeling process, aiding in the prediction of structural behavior. It's worth noting that there is a dearth of experimental studies addressing the influence of geometric defects on the buckling behavior of cylindrical steel shells. In this particular study, samples featuring geometric imperfections were subjected to experimental buckling tests. These same samples were also modeled using Finite Element Analysis (FEM), with results corroborating the experimental findings. Furthermore, the initial geometrical imperfections were measured using digital image correlation (DIC) techniques. In this way, the response of the test specimens can be estimated accurately by applying the initial imperfections to FE models. After validation of the test results with FEA, a numerical parametric study was conducted to develop more generalized design recommendations for the stainless-steel shell structures with the initial geometric imperfection. While the load-carrying capacity of samples with perfect surfaces was up to 140 kN, the load-carrying capacity of samples with 4 mm defects was around 130 kN. Likewise, while the load carrying capacity of samples with 10 mm defects was around 125 kN, the load carrying capacity of samples with 14 mm defects was measured around 120 kN.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.36 no.2
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• pp.50-60
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• 2024

To promote the application of reliability-based design within the Korean coastal engineering community, the author conducted reliability analyses and optimized the design of a vertical-type breakwater, considering multiple limit states in the seas off of Pusan and Gunsan - two representative ports in Korea. In this process, rather than relying on design waves of a specific return period, the author intentionally avoided such constraints. Instead, the author characterized the uncertainties associated with wave force, lift force, and overturning moment - key factors significantly influencing the integrity of a vertical-type breakwater. This characterization was achieved by employing a probabilistic model derived from the frequency analysis results of long-term in-situ wave data. The limit state of the vertical-type breakwater encompassed sliding, overturning, and collapse failure, with the close interrelation between wave force, lift force, and moment described using the Nataf joint probability distribution. Simulation results indicate, as expected, that considering only sliding failure underestimates the failure probability. Furthermore, it was shown that the failure probability of vertical-type breakwaters cannot be consistently secured using design waves with a specific return period. In contrast, breakwaters optimally designed to meet the reliability index requirement of 𝛽-3.5 to 4 consistently achieve a consistent failure probability across all sea areas.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.6
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• pp.67-84
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• 2023

In some areas of the Republic of Korea, the designation and management of conservation areas do not adequately reflect regional characteristics and often impose behavioral regulations without considering the local context. One prominent example is the Busan EDC area. As a result, conflicts may arise, including large-scale civil complaints, regarding the conservation and utilization of these areas. Therefore, for the efficient designation and management of protected areas, it is necessary to consider various ecosystem factors, changes in land use, and regional characteristics. In this study, we specifically focused on the Busan EDC area and applied machine learning techniques to analyze the habitat of regional species. Additionally, we employed Explainable Artificial Intelligence techniques to interpret the results of our analysis. To analyze the regional characteristics of the waterfront area in the Busan EDC district and the habitat of migratory birds, we used bird observations as dependent variables, distinguishing between presence and absence. The independent variables were constructed using land cover, elevation, slope, bridges, and river depth data. We utilized the XGBoost (eXtreme Gradient Boosting) model, known for its excellent performance in various fields, to predict the habitat probabilities of 11 bird species. Furthermore, we employed the SHapley Additive exPlanations technique, one of the representative methodologies of XAI, to analyze the relative importance and impact of the variables used in the model. The analysis results showed that in the EDC business district, as one moves closer to the river from the waterfront, the likelihood of bird habitat increases based on the overlapping habitat probabilities of the analyzed bird species. By synthesizing the major variables influencing the habitat of each species, key variables such as rivers, rice fields, fields, pastures, inland wetlands, tidal flats, orchards, cultivated lands, cliffs & rocks, elevation, lakes, and deciduous forests were identified as areas that can serve as habitats, shelters, resting places, and feeding grounds for birds. On the other hand, artificial structures such as bridges, railways, and other public facilities were found to have a negative impact on bird habitat. The development of a management plan for conservation areas based on the objective analysis presented in this study is expected to be extensively utilized in the future. It will provide diverse evidential materials for establishing effective conservation area management strategies.

• Journal of Radiation Industry
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• v.17 no.4
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• pp.471-479
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• 2023

In In-situ radioactivity measurement techniques, efficiency calibration models use predefined models to simulate a sample's geometry and radioactivity distribution. However, simplified efficiency calibration models lead to uncertainties in the efficiency curves, which in turn affect the radioactivity concentration results. This study aims to develop an efficiency calibration optimization methodology to improve the accuracy of in-situ gamma radiation measurements for byproducts from industrial facilities. To accomplish the objective, a drive mechanism for rotational measurement of an byproduct simulator and a sample was constructed. Using ISOCS, an efficiency calibration model of the designed object was generated. Then, the sensitivity analysis of the efficiency calibration model was performed, and the efficiency curve of the efficiency calibration model was optimized using the sensitivity analysis results. Finally, the radiation concentration of the simulated subject was estimated, compared, and evaluated with the designed certification value. For the sensitivity assessment of the influencing factors of the efficiency calibration model, the ISOCS Uncertainty Estimator was used for the horizontal and vertical size and density of the measured object. The standard deviation of the measurement efficiency as a function of the longitudinal size and density of the efficiency calibration model decreased with increasing energy region. When using the optimized efficiency calibration model, the measurement efficiency using IUE was improved compared to the measurement efficiency using ISOCS at the energy of ²²⁸Ac (911 keV) for the nuclide under analysis. Using the ISOCS efficiency calibration method, the difference between the measured radiation concentration and the design value for each simulated subject measurement direction was 4.1% (1% to 10%) on average. The difference between the estimated radioactivity concentration and the design value was 3.6% (1~8%) on average when using the ISOCS IUE efficiency calibration method, which was closer to the design value than the efficiency calibration method using ISOCS. In other words, the estimated radioactivity concentration using the optimized efficiency curve was similar to the designed radioactivity concentration. The results of this study can be utilized as the main basis for the development of regulatory technologies for the treatment and disposal of waste generated during the operation, maintenance, and facility replacement of domestic byproduct generation facilities.

• Journal of Industrial Convergence
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• v.22 no.8
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• pp.63-72
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• 2024

This study attempted to explore the impact of sense of humor and stress coping styles among nursing students on adaptation to clinical practice. The study included 180 nursing students as participants, and data collection was conducted using self-administered questionnaires from April 15 to 26, 2024. The collected data underwent t-test, one-way ANOVA, Pearson's correlation coefficients, and multiple regression analysis. The research findings revealed that the sense of humor scored 3.52, stress coping styles scored 3.40, and adaptation to clinical practice scored 3.46. Adaptation to clinical practice according to general characteristics showed statistically significant differences based on major satisfaction (F=29.80, p<.001), clinical practice satisfaction (F=40.46, p<.001), relationships with peers in clinical practice (F=5.05, p<.001), and personality (t=-3.41, p<.05). Adaptation to clinical practice showed statistically significant positive correlations with sense of humor (r=.31, p<.001) and stress coping styles (r=.43, p<.001). The factors influencing adaptation to clinical practice were clinical practice satisfaction(β=.34, p<.001), stress coping styles (β=.29, p<.001), and major satisfaction (β=.23, p<.05), explaining 42% of the total variance.

• Science of Emotion and Sensibility
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• v.27 no.2
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• pp.69-80
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• 2024

The COVID-19 pandemic highlighted the importance of remote education, yet the adoption rate of AI in the educational sector remains relatively low, and studies into learners' familiarity with using AI learning robots are scarce. In response, this study analyzes the factors influencing users' familiarity with AI learning robots in a smart learning environment tailored to the untact era. To this end, social big data analysis was used to examine changes in public perception and the frequency of mentions of smart learning and AI learning robots. The results showed that positive perceptions of smart learning significantly outweigh negative ones, reflecting the convenience and improved accessibility that technology brings to education. However, there is also a considerable negative perception attached to smartphone use, which is interpreted as reflecting concerns that smartphones may disrupt learning and bring other negative aspects of technology dependence. These results indicate mixed social concerns and expectations regarding the educational use of smart learning and AI technologies. The effective introduction and use of AI learning robots, especially in smart learning environments, necessitate considering these social perceptions. This study provides foundational data for the effective implementation and use of AI learning robots in smart learning environments and suggests the need for approaches that primarily consider users' familiarity and social perceptions in the development of educational technologies.