• Journal of the Society of Naval Architects of Korea
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• v.28 no.1
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• pp.150-168
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• 1991

A practical procedure for the ultimate compressive strength-based safety and reliability assessment of the double skin upper deck structure is described. The external compressive stress acting on the upper deck structure which is due to the still water and wave-induced sagging moment is approximately estimated by using the existing rule of classification society. The ultimate compressive stress of double skin structure under the action of sagging moment is analyzed by using idealized structural unit method. Here an idealized plate element subjected to uniaxial load is formulated by idealizing the nonlinear behaviour of the actual element taking account of the initial imperfections in the form of initial deflection and welding residual stress. The interaction effect between the local and global failure in the structure is also taken into consideration. The accuracy of the present method is verified comparing with the present solution and the existing numerical and experimental results for unit member and welded box columns. The safety of the structure is evaluated using the concept of conventional central safety factor and the reliability assessment is made by using Cornel's MVFOSM method. The present procedure is then applied to upper deck structure of double skin product oil carrier. The influence of the initial imperfections and the yield stress of the material on the safety and reliability of the structure is investigated.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.1-7
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• 2017

In general, the large loads which are applied from explosion, impact, earthquake and wind at a short time caused the materials of structures to large deformations, rotations and strains locally. If such phenomena will be analyzed, hydrocodes which can be considered fluid-structure interaction under computational continuum mechanics are inevitably needed. Also, the explosion mechanism is so complicated, it is reasonable that the behaviors of structure are predicted through explosion analyses and experiment at the same time. But, unfortunately, it is true that explosion experiments are limited to huge cost, large experiment facilities and safety problems. Therefore, in this study, it is shown that the results of explosion analyses using the AUTODYN are agreed with those of existing explosion experiments for reinforced concrete slabs within reasonable error limits. And the explosion damage of the same reinforced concrete slab are assessed for quite different reinforcement arrangement spacings, concrete cover depths, and vertical reinforcements. From the explosion analyses, it is known that the more the ratio of slab thickness to reinforcement arrangement spacing is increased, and small-diameter reinforcements are used than large-diameter reinforcements on the same reinforcement ratio, and vertical reinforcements are used, the more the anti-knock capacities are improved.

• Journal of Korean Elementary Science Education
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• v.40 no.1
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• pp.22-35
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• 2021

In order to investigate the trends in science education research using AR (Augmented Reality) and derive implications for elementary science education, we analyzed 71 research articles on AR application in science education published in both Korea and abroad from 2010 to August 2020. In quantitative aspects, the number of published articles has steadily increased. For domestic researches, the number of papers targeting for elementary school students was higher than that of middle & high school students. In the research method aspects, qualitative methods were most frequently used. In particular, papers regarding the development of AR program and verification of its effectiveness were most frequently published. The researches using mixed method in domestic field were smaller in number than that of the research in abroad. There were similar trends in research targeting elementary school students. In the aspects of the contents, more researches were performed on biology and earth science areas than others. In case of researches for elementary school students, the proportion of researches on biology and earth science was even higher. Domestically the proportion of studies on the convergence of science and non-science subjects was higher than that of foreign studies. The number of researches exploring the effectiveness on 'non-scientific attitude domain', 'cognitive domain', and 'program domain' were relatively higher than that on 'inquiry & practice domain' and 'science-related attitude domain'. For types of AR contents, 'observation manipulation type' was mostly studied, followed by 'experimental activity type', and 'learning guide type'. In case of studies on elementary school students, the ratio of 'observation manipulation type' contents was higher than that of others, whereas studies on 'field problem solving type' were relatively less reported than others. In addition, studies on 'simple interaction' were most frequently reported. Particularly, there were relatively few studies on 'linear and nonlinear interactions' in domestic field. As a result of analyzing key words, we found that the key words related to the characteristics and implementation of AR frequently occurred, and the key words related to elementary education and the merits of AR had many direct connections with other key words.

• Geophysics and Geophysical Exploration
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• v.24 no.2
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• pp.53-66
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• 2021

Velocity model building is an essential procedure in seismic data processing. Conventional techniques, such as traveltime tomography or velocity analysis take longer computational time to predict a single velocity model and the quality of the inversion results is highly dependent on human expertise. Full-waveform inversions also depend on an accurate initial model. Recently, deep neural network techniques are gaining widespread acceptance due to an increase in their integration to solving complex and nonlinear problems. This study investigated cases of seismic velocity model building using deep neural network techniques by classifying items according to the neural networks used in each study. We also included cases of generating training synthetic velocity models. Deep neural networks automatically optimize model parameters by training neural networks from large amounts of data. Thus, less human interaction is involved in the quality of the inversion results compared to that of conventional techniques and the computational cost of predicting a single velocity model after training is negligible. Additionally, unlike full-waveform inversions, the initial velocity model is not required. Several studies have demonstrated that deep neural network techniques achieve outstanding performance not only in computational cost but also in inversion results. Based on the research results, we analyzed and discussed the characteristics of deep neural network techniques for building velocity models.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.21-33
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• 2022

Recently, the recommender system has been widely used in various fields such as movies, music, online shopping, and social media, and in the meantime, the recommender model has been developed from correlation analysis through the Apriori model, which can be said to be the first-generation model in the recommender system field. In 2005, many models have been proposed, including deep learning-based models, which are receiving a lot of attention within the recommender model. The recommender model can be classified into a collaborative filtering method, a content-based method, and a hybrid method that uses these two methods integrally. However, these basic methods are gradually losing their status as methodologies in the field as they fail to adapt to internal and external changing factors such as the rapidly changing user-item interaction and the development of big data. On the other hand, the importance of deep learning methodologies in recommender systems is increasing because of its advantages such as nonlinear transformation, representation learning, sequence modeling, and flexibility. In this paper, among deep learning methodologies, RNN, CNN, and GAN-based models suitable for sequential modeling that can accurately and flexibly analyze user-item interactions are classified, compared, and analyzed.

• Journal of Preventive Medicine and Public Health
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• v.56 no.3
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• pp.282-290
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• 2023

Objectives: This study aimed to evaluate the potential interaction between kidney function and the non-linear association between serum calcium levels and cardiovascular disease (CVD) mortality. Methods: This study included 8927 participants enrolled in the Dong-gu Study. Albumin-corrected calcium levels were used and categorized into 6 percentile categories: <2.5th, 2.5-25.0th, 25.0-50.0th, 50.0-75.0th, 75.0-97.5th, and >97.5th. Restricted cubic spline analysis was used to examine the non-linear association between calcium levels and CVD mortality. Cox proportional hazard regression was used to estimate hazard ratios (HRs) for CVD mortality according to serum calcium categories. All survival analyses were stratified by the estimated glomerular filtration rate. Results: Over a follow-up period of 11.9±2.8 years, 1757 participants died, of whom 219 died from CVD. A U-shaped association between serum calcium and CVD mortality was found, and the association was more evident in the low kidney function group. Compared to the 25.0-50.0th percentile group for serum calcium levels, both low and high serum calcium tended to be associated with CVD mortality (<2.5th: HR, 6.23; 95% confidence interval [CI], 1.16 to 33.56; >97.5th: HR, 2.56; 95% CI, 0.76 to 8.66) in the low kidney function group. In the normal kidney function group, a similar association was found between serum calcium levels and CVD mortality (<2.5th: HR, 1.37; 95% CI, 0.58 to 3.27; >97.5th: HR, 1.65; 95% CI, 0.70 to 3.93). Conclusions: We found a non-linear association between serum calcium levels and CVD mortality, suggesting that calcium dyshomeostasis may contribute to CVD mortality, and kidney function may modify the association.

• Korean Journal of Culture and Social Issue
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• v.29 no.4
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• pp.617-636
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• 2023

The goal of this study was to explain the phenomenon of making efforts to overcome the need-reality collision as a cultural characteristic of Koreans. Specifically, we examined whether the behavior varies depending on the degree of relational agency in the situation where conflicts between one's needs and reality have occurred. To this end, a total of 217 participants participated in the online experiment, and the data of 156 participants were finally analyzed. After responding to the relational agency scale, the participants were exposed to a decision-making scenario in which conflicting factors existed. The scenario were about buying a house and making a wedding hall contract, and in each scenario, two important values were set to conflict with each other in the market. Participants read the scenario and entered the level they wanted for each value. After that, they encounter a situation in which he or she has not found the candidate site corresponding to the level he or she wants. Then, the participants responded to their willingness to make additional efforts themselves. As a result of the study, the degree of relational agency of the participants showed a positive relationship with the degree of additional effort. In addition, the degree of the desired level beyond the reality (expectancy discrepancy) showed a nonlinear (reverse U-shape) influence on the additional effort while controlling for individual difference. Furthermore, the interaction effect between relational agency and expectancy discrepancy was significant. Specifically, individuals with low agency did not have a significant relationship between the degree of expectancy discrepancy and the dependent variable, but individuals with high relational agency had a significant non-linear relationship between the degree of expectancy discrepancy and the dependent variable. Based on the results of the study, the role and function of Koreans' psychological characteristics (relational agency) in the scene of managing needs-reality collision were discussed.

• Journal of the Korean Geotechnical Society
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• v.39 no.5
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• pp.51-63
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• 2023

Numerical analysis was conducted to determine the effect of soil behavior by thawing and freezing of seasonal frozen soil on pile foundations. The analysis was performed using the finite element method (FEM) to simulate soil-pile interaction based on the atmosphere temperature change. Thermomechanical coupled modeling using FEM was applied with the temperature-dependent nonlinear properties of the frozen soil. The analysis model cases were applied to the MCR and HDP models to simulate the elastoplastic behavior of soil. The numerical analysis results were analyzed and compared with various conditions having different length and width sizes of the pile. The results of the numerical analysis showed t hat t he HDP model was relat ively passive, and t he aspect and magnit ude of t he bearing capacit y and displacement of the pile head were similar depending on the length and width of the pile conditions. The vertical displacement of the pile head by thawing and freezing of the ground showed a large variation in displacement for shorter length conditions. In the MCR model, the vertical displacement appeared in the maximum thaw settlement and frost heaving of 0.0387 and 0.0277 m, respectively. In the HDP model, the vertical displacement appeared in the maximum thaw settlement and frost heaving of 0.0367 and 0.0264 m, respectively. The results of the pile bearing capacity for the two elastoplastic models showed a larger difference in the width condition than the length condition of the pile, with a maximum of about 14.7% for the width L condition, a maximum of about 5.4% for M condition, and a maximum of about 5.3% for S condition. The significance of the effect on the displacement of the pile head and the bearing capacity depended on the pile-soil contact area, and the difference depended on the presence or absence of an active layer in the soil and its thickness.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.341-346
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• 2009

The motion data glove is a representative human-computer interaction tool that inputs human hand gestures to computers by measuring their motions. The motion data glove is essential equipment used for new computer technologiesincluding home automation, virtual reality, biometrics, motion capture. For its popular usage, this paper attempts to develop an inexpensive visual.type motion data glove that can be used without any special equipment. The proposed approach has the special feature; it can be developed as a low-cost one becauseof not using high-cost motion-sensing fibers that were used in the conventional approaches. That makes its easy production and popular use possible. This approach adopts a visual method that is obtained by improving conventional optic motion capture technology, instead of mechanical method using motion-sensing fibers. Compared to conventional visual methods, the proposed method has the following advantages and originalities Firstly, conventional visual methods use many cameras and equipments to reconstruct 3D pose with eliminating occlusions But the proposed method adopts a mono vision approachthat makes simple and low cost equipments possible. Secondly, conventional mono vision methods have difficulty in reconstructing 3D pose of occluded parts in images because they have weak points about occlusions. But the proposed approach can reconstruct occluded parts in images by using originally designed thin-bar-shaped optic indicators. Thirdly, many cases of conventional methods use nonlinear numerical computation image analysis algorithm, so they have inconvenience about their initialization and computation times. But the proposed method improves these inconveniences by using a closed-form image analysis algorithm that is obtained from original formulation. Fourthly, many cases of conventional closed-form algorithms use approximations in their formulations processes, so they have disadvantages of low accuracy and confined applications due to singularities. But the proposed method improves these disadvantages by original formulation techniques where a closed-form algorithm is derived by using exponential-form twist coordinates, instead of using approximations or local parameterizations such as Euler angels.