• Steel and Composite Structures
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• v.32 no.4
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• pp.423-441
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• 2019

This study aims to accurately predict the first ply failure loads of laminated composite hypar shell roofs with different boundary conditions. The geometrically nonlinear finite element method (FEM) is used to analyse different symmetric and anti-symmetric, cross and angle ply shells. The first ply failure loads are obtained through different well-established failure criteria including Puck's criterion along with the serviceability criterion of deflection. The close agreement of the published and present results for different validation problems proves the correctness of the finite element model used in the present study. The effects of edge conditions on first ply failure behavior are discussed critically from practical engineering point of view. Factor of safety values and failure zones are also reported to suggest design and non-destructive monitoring guidelines to practicing engineers. Apart from these, the present study indicates the rank wise relative performances of different shell options. The study establishes that the angle ply laminates in general perform better than the cross ply ones. Among the stacking sequences considered here, three layered symmetric angle ply laminates offer the highest first ply failure load. The probable failure zones on the different shell surfaces, identified in this paper, are the areas where non-destructive health monitoring may be restricted to. The contributions made through this paper are expected to serve as important design aids to engineers engaged in composite hypar shell design and construction.

• Journal of Korea Multimedia Society
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• v.22 no.1
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• pp.35-43
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• 2019

Template tracking refers to the procedure of finding the most similar image patch corresponding to the given template through an image sequence. In order to obtain more accurate trajectory of the template, the template requires to be updated to reflect various appearance changes as it traverses through an image sequence. To do that, appearance images are used to model appearance variations and these are obtained by the computation of the principal components of the augmented image matrix at every iteration. Unfortunately, it is prohibitively expensive to compute the principal components at every iteration. Thus in this paper, we suggest a new Sliding Window based truncated URV Decomposition (TURVD) algorithm which enables updating their structure by recycling their previous decomposition instead of decomposing the image matrix from the beginning. Specifically, we show an efficient algorithm for updating and downdating the TURVD simultaneously, followed by the rank-one update to the TURVD while tracking the decomposition error accurately and adjusting the truncation level adaptively. Experiments show that the proposed algorithm produces no-meaningful differences but much faster execution speed compared to the typical algorithms in template tracking applications, thereby maintaining a good approximation for the principal components.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.136-150
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• 2021

The modern market is highly competitive. It has progressed from traditional competition between enterprises to competition between supply chains. To ensure that enterprise can form the best strategy consistently, it is necessary to evaluate the trust of other enterprises in the supply chain. First, this paper analyzes the background and significance of supply chain trust research, analyzes and expounds on the qualitative and quantitative methods of supply chain trust evaluation, and summarizes the research in this field. Analytic hierarchy process (AHP) is the most frequently used method in the literature to evaluate and rank criteria through data analysis. However, the input data for AHP analysis is based on human judgment, and hence there is every possibility that the data may be vague to some extent. Therefore, in view of the above problems, this study improves the global trust method based on chain iteration. The improved global trust evaluation method based on chain iteration is more flexible and practical, hence, it can more accurately evaluate supply chain trust. Finally, combined with an actual case of Zhaoxian Chengji Food Co. Ltd., the paper qualitatively analyzes the current situation of supply chain trust management and effectively strengthens the supervision of enterprises to cooperative enterprises. Thus, the company can identify problems on time and strategic adjustments can be implemented accordingly. The effectiveness of the evaluation method proposed in this paper is demonstrated through a quantitative evaluation of its trust in downstream enterprise A. Results suggest that the subjective preferences of and historical transactions together affect the final evaluation of trust.

• The korean journal of orthodontics
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• v.52 no.4
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• pp.258-267
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• 2022

Objective: This study aimed to evaluate the superimposition accuracy of digital modes for measuring tooth movement in patients requiring anterior retraction after premolar extraction based on the proposed reference regions. Methods: Forty patients treated with bilateral maxillary first premolar extraction were divided into two groups: moderate retraction (< 7.0 mm) and maximum retraction (≥ 7.0 mm). Central incisor displacement was measured using cephalometric superimpositions and three-dimensional (3D) digital superimpositions with the 3rd or 4th ruga as the reference point. The Wilcoxon signed-rank test and linear regression analyses were performed to test the significance of the differences and relationships between the two measurement techniques. Results: In the moderate retraction group, the central incisor anteroposterior displacement values did not differ significantly between 3D digital and cephalometric superimpositions. However, in the maximum-retraction group, significant differences were observed between the anteroposterior displacement evaluated by the 3rd ruga superimposition and cephalometric methods (p < 0.05). Conclusions: This study demonstrated that 3D digital superimpositions were clinically as reliable as cephalometric superimpositions in assessing tooth movements in patients requiring moderate retraction. However, the reference point should be carefully examined in patients who require maximum retraction.

• Biomedical Science Letters
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• v.29 no.4
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• pp.355-362
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• 2023

This study aimed to determine whether smoking affects the metabolic syndrome and its components through long-term follow-up. Of the 10,030 cohort subjects in the community-based Korean Genome and Epidemiology Study (KoGES) from 2001 to 2018, 2,848 people with metabolic syndrome and 4,854 people with insufficient data for analysis were excluded for this study. The study population comprised 2,328 individuals (1,123 men, 1,205 women) who were eligible for inclusion. The mean age of the participants was 49.2±7.5 years, and 21.9% were current smoker. In log rank test, current smoker had a significantly higher cumulative incidence of metabolic syndrome compared with non smoker (P<0.001). In the Cox proportional hazards model adjusted for key variables, metabolic syndrome (hazard ratio [HR] 1.57, P<0.001), high fasting glucose (HR 1.40, P<0.01), hypertriglyceridemia (HR 1.60, P<0.001), low HDL-cholesterol (HR, 1.30, P<0.01), and abdominal obesity (HR 1.32, P<0.01) in current smoker compared with non smoker were statistically significant, respectively, but not hypertension (HR 1.00, P>0.05). After adjustment for confounders, the time (P-time<0.001) and group (P-group<0.001) effects on metabolic syndrome score change were statistically significant. Furthermore, the interaction analysis of time and smoking group on the change in metabolic syndrome score was statistically significant (P-interaction<0.001). In long-term follow-up, smoking worsens metabolic syndrome.

• The Journal of Economics, Marketing and Management
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• v.12 no.1
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• pp.17-28
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• 2024

Purpose: This paper is designed to deliver a deeper understanding of the implications of digitalization strategies in the tourism industry, exploring the opportunities and challenges in South Korea. Research design, data and methodology: To identify effective strategies, an integrated approach is employed in the research that encompasses the Glocal RPM analysis and SANEL HERMES model, as well as the examination of digital tourism factors within the DIANA economy. The data used for this study were derived from multiple sources, including literature review, participation interview, tourist survey and expert questionnaire. By conducting a tourist survey using questionnaires in this research, Glocal RPM and SANEL HERMES hybrid method is used identifying and classifying influencing factors limiting digitalization in tourism. As a final step, experts use a Quantitative Strategic Planning Matrix to propose, assess, and rank a number of digitalization strategies. Results: According to the analysis, the study revealed that combining both tools contributes to a more holistic understanding of the environment, uncovering the positives and negatives from diverse perspectives. The average satisfaction percentage of experts was determined to be 38%, indicating anatal level of digitalization for tourism industry in South Korea. Conclusions: These results can serve as a valuable guide for policymakers and stakeholders in formulating targeted strategies to enhance glocalization, rationality, professionalism, and morality within the digitalization context.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.395-418
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• 2024

The epicentral region of earthquakes is typically where liquefaction-related damage takes place. To determine the maximum distance, such as maximum epicentral distance (R_e), maximum fault distance (R_f), or maximum hypocentral distance (R_h), at which an earthquake can inflict damage, given its magnitude, this study, using a recently updated global liquefaction database, multiple ML models are built to predict the limiting distances (R_e, R_f, or R_h) required for an earthquake of a given magnitude to cause damage. Four machine learning models LSTM (Long Short-Term Memory), BiLSTM (Bidirectional Long Short-Term Memory), CNN (Convolutional Neural Network), and XGB (Extreme Gradient Boosting) are developed using the Python programming language. All four proposed ML models performed better than empirical models for limiting distance assessment. Among these models, the XGB model outperformed all the models. In order to determine how well the suggested models can predict limiting distances, a number of statistical parameters have been studied. To compare the accuracy of the proposed models, rank analysis, error matrix, and Taylor diagram have been developed. The ML models proposed in this paper are more robust than other current models and may be used to assess the minimal energy of a liquefaction disaster caused by an earthquake or to estimate the maximum distance of a liquefied site provided an earthquake in rapid disaster mapping.

• Korean Chemical Engineering Research
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• v.52 no.4
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• pp.544-552
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• 2014

In this study, We have investigated the kinetics on the char-$CO_2$ gasification reaction. Thermogravimetric analysis (TGA) experiments were carried out for char-$CO_2$ catalytic gasification of an Indonesian Roto lignite. $Na_2CO_3$, $K_2CO_3$, $CaCO_3$ and dolomite were selected as catalyst which was physical mixed with coal. The char-$CO_2$ gasification reaction showed rapid an increase of carbon conversion rate at 60 vol% $CO_2$ and 7 wt% $Na_2CO_3$ mixed with coal. At the isothermal conditions range from $750^{\circ}C$ to $900^{\circ}C$, the carbon conversion rates increased as the temperature increased. Three kinetic models for gas-solid reaction including the shrinking core model (SCM), volumetric reaction model (VRM) and modified volumetric reaction model (MVRM) were applied to the experimental data against the measured kinetic data. The gasification kinetics were suitably described by the MVRM model for the Roto lignite. The activation energies for each char mixed with $Na_2CO_3$ and $K_2CO_3$ were found a 67.03~77.09 kJ/mol and 53.14~67.99 kJ/mol.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.27-37
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• 2008

Applications of 3D data increase with advancement of multimedia technique and contents, and it is necessary to manage and to retrieve for 3D data efficiently. In this paper, we propose a new method using the sliced shape which extracts efficiently a feature description for shape-based retrieval of 3D models. Since the feature descriptor of 3D model should be invariant to translation, rotation and scale for its model, normalization of models requires for 3D model retrieval system. This paper uses principal component analysis(PCA) method in order to normalize all the models. The proposed algorithm finds a direction of each axis by the PCA and creates orthogonal n planes in each axis. These planes are orthogonalized with each axis, and are used to extract sliced shape image. Sliced shape image is the 2D plane created by intersecting at between 3D model and these planes. The proposed feature descriptor is a distribution of Euclidean distances from center point of sliced shape image to its outline. A performed evaluation is used for average of the normalize modified retrieval rank(ANMRR) with a standard evaluation from MPEG-7. In our experimental results, we demonstrate that the proposed method is an efficient 3D model retrieval.

• Journal of agriculture & life science
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• v.44 no.2
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• pp.29-38
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• 2010

This study looked into estimation of variance component over swine's economic traits by multiple animal model and maternal effect model using on-farm test data of total 31,455 swine of Duroc, Landrace and Yorkshire species that were born between 2000 and 2008. Heritability by estimated additive genetic effect showed higher than one by maternal genetic effect using multivariate maternal animal model in each trait examined by each breed and most heritability when considering only additive genetic effect in multiple traits animal model was estimated to be higher than one by estimated additive genetic effect in multivariate maternal animal model. In correlation between breeding value by estimated maternal genetic effect and phenotypic value using multivariate maternal animal model, rank correlation and simple correlation of breeding value and phenotypic value by maternal genetic effect also showed low positive correlation or strong negative correlation, which can be considered that if correlation with phenotype were increased properly considering maternal genetic effect in each trait by each breed, even better improvement could be promoted.