• Journal of the Korean Geotechnical Society
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• v.22 no.2
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• pp.41-53
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• 2006

The brittle materials like rocks show complicated strain-softening behavior after the peak which is hard to model using the classical constitutive models based on the relation between strain and stress tensors. A kinematically constrained three-dimensional microplane constitutive model is developed for granite. The model is verified by fitting the experimented data of Westerly granite and Bonnet granite. The triaxial behavior of granite is well reproduced by the model as well as the uniaxial behavior. We studied the development of the fracture zone in granite during blasting impact using the model with the standard finite element method. All the results obtained from the microplane model developed are compared to those from the linear elasticity model which is commonly used in many researches and practices. It is found that the nonlinearity of rocks sigificantly affects the results of analysis.

• Korean Journal of Veterinary Service
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• v.46 no.1
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• pp.59-66
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• 2023

Wild boar is closely related to domestic pigs in terms of genetic homogeneity and the possibility of a source of infection by contact. This study investigated the prevalence of viral diseases from wild boars inhabiting Gyeongsangnam-do, South Korea. A total of 374 blood samples were collected and subjected to antigen tests to detect African swine fever virus (ASFV), Porcine circovirus type-2 (PCV2), Porcine reproductive and respiratory syndrome virus (PRRSV). For seroprevalence, PCV2, PRRS, classical swine fever virus (CSFV), Aujezsky's disease (ADV), and foot and mouth disease virus (FMDV) were investigated. The antigenic analysis revealed 73 positive cases (19.5%) for PCV2, while no positive cases for ASFV and PRRSV. For the antibody test, 225 (60.2%), 2 (0.5%), and 48 (12.8%) cases were detected against PCV2, PRRSV, and CSFV, respectively. There were no antibodies detected against both ADV and FMDV. Our results suggest that the viruses infecting both wild boar and domestic pig, mainly PCV2, are circulating in the wild boar population thus, the consistent monitoring of prevalence in wild boar will be needed for transboundary spillover to the domestic pig.

• Communications for Statistical Applications and Methods
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• v.30 no.2
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• pp.119-133
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• 2023

With the rapid growth of the economy and fossil fuel consumption, the concentration of air pollutants has increased significantly and the air pollution problem is no longer limited to small areas. We conduct statistical analysis with the actual data related to air quality that covers the entire of South Korea using R and Python. Some factors such as SO₂, CO, O₃, NO₂, PM₁₀, precipitation, wind speed, wind direction, vapor pressure, local pressure, sea level pressure, temperature, humidity, and others are used as covariates. The main goal of this paper is to predict air quality index (AQI) spatio-temporal data. The observations of spatio-temporal big datasets like AQI data are correlated both spatially and temporally, and computation of the prediction or forecasting with dependence structure is often infeasible. As such, the likelihood function based on the spatio-temporal model may be complicated and some special modelings are useful for statistically reliable predictions. In this paper, we propose several methods for this big spatio-temporal AQI data. First, random effects with spatio-temporal basis functions model, a classical statistical analysis, is proposed. Next, neural networks model, a deep learning method based on artificial neural networks, is applied. Finally, random forest model, a machine learning method that is closer to computational science, will be introduced. Then we compare the forecasting performance of each other in terms of predictive diagnostics. As a result of the analysis, all three methods predicted the normal level of PM_2.5 well, but the performance seems to be poor at the extreme value.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.65-72
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• 2009

This study presents a structural design optimizing sizes of high-rise steel plane truss members by maximizing stiffness subjected to given volume constraints. The sizing optimum design is evaluated by using a well-known optimality criteria (OC) of gradient-based optimization methods. In typical size optimization methods, truss structures are optimized with respect to minimum weight with constraints on the value of some displacement and on the member stresses. The proposed method is an inversed size optimization process in comparisons with the typical size optimization methods since it maximizes stiffness associated with stresses or displacements subjected to volume constraints related to weight. The inversed approach is another alternative to classical size optimization methods in order to optimize members' sizes in truss structures. Numerical applications of a round shape steel pipe truss structure are studied to verify that the proposed maximum stiffness-based size optimization design is suitable for optimally developing truss members's sizes.

• Korea Trade Review
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• v.42 no.1
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• pp.189-215
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• 2017

This study analyzes the determinants of the choice of foreign direct investment mode by Korean fashion firms in entering into foreign markets. We have established hypotheses regarding their choice among three classical entry modes including a wholly-owned subsidiary, a joint venture and an M&A based on factors such as the investing firm's size, international experience and international strategy type, host market potentials, cultural distance and foreign investment risk. By conducting multiple logistic regression over secondary data on 100 Korean fashion firms, we found that all variables but cultural distance were statistically significant. The results may contribute to advancing international business theory on the fashion industry and developing fashion firms' global strategy.

• Structural Engineering and Mechanics
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• v.86 no.5
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• pp.647-661
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• 2023

It is recognized that the installation of energy dissipation devices, such as the tuned mass damper (TMD), decreases the dynamic response of structures, however, the best parameters of each device persist hard to determine. Unlike many works that perform only a deterministic optimization, this work proposes a complete methodology to minimize the dynamic response of footbridges by optimizing the parameters of multiple tuned mass dampers (MTMD) taking into account uncertainties present in the parameters of the structure and also of the human excitation. For application purposes, a steel footbridge, based on a real structure, is studied. Three different scenarios for the MTMD are simulated. The proposed robust optimization problem is solved via the Circle-Inspired Optimization Algorithm (CIOA), a novel and efficient metaheuristic algorithm recently developed by the authors. The objective function is to minimize the mean maximum vertical displacement of the footbridge, whereas the design variables are the stiffness and damping constants of the MTMD. The results showed the excellent capacity of the proposed methodology, reducing the mean maximum vertical displacement by more than 36% and in a computational time about 9% less than using a classical genetic algorithm. The results obtained by the proposed methodology are also compared with results obtained through traditional TMD design methods, showing again the best performance of the proposed optimization method. Finally, an analysis of the maximum vertical acceleration showed a reduction of more than 91% for the three scenarios, leading the footbridge to acceleration values below the recommended comfort limits. Hence, the proposed methodology could be employed to optimize MTMD, improving the design of footbridges.

• Steel and Composite Structures
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• v.47 no.6
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• pp.693-707
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• 2023

This article investigates the static thermo-mechanical response of anisotropic thick laminated composite plates on Visco-Pasternak foundations under various thermal load conditions (linear, non-linear, and uniform) along the transverse direction (thickness) of the plate, while keeping the mechanical load constant. The governing equations, which represent the thermo-mechanical behavior of the composite plate, are derived from the principle of virtual displacements. Using Navier's type solution, these equations are solved for the composite plate with simply supported condition. The Visco-Pasternak foundation type is included by considering the impact of the damping on the classical foundation model, which is modeled by Winkler's linear modulus and Pasternak's shear modulus. The excellent accuracy of the present solution is confirmed by comparing the results with those available in the literature. The study investigates the impact of geometric ratios, thermal expansion coefficient ratio, damping coefficient and foundation parameters on the thermo-mechanical flexural response of the composite plate. Overall, this article provides insights into the behavior of composite plates on visco-Pasternak foundations and may be useful for designing and analyzing composite structures in practical applications.

• Animal Bioscience
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• v.36 no.9
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• pp.1435-1444
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• 2023

Objective: This study was conducted to evaluate Raman spectroscopy technique as a noninvasive tool to predict meat quality traits on Braford longissimus thoracis et lumborum muscle. Methods: Thirty samples of muscle from Braford steers were analyzed by classical meat quality techniques and by Raman spectroscopy with 785 nm laser excitation. Water holding capacity (WHC), intramuscular fat content (IMF), cooking loss (CL), and texture profile analysis recording hardness, cohesiveness, and chewiness were determined, along with fiber diameter and sarcomere length by scanning electron microscopy. Warner-Bratzler shear force (WBSF) analysis was used to differentiate tender and tough meat groups. Results: Higher values of cohesiveness and CL, together with lower values of WHC, IMF, and shorter sarcomere were obtained for tender meat samples than for the tougher ones. Raman spectra analysis allows tender and tough sample differentiation. The correlation between the quality attributes predicted by Raman and the physical measurements resulted in values of R² = 0.69 for hardness and 0,58 for WBSF. Pearson's correlation coefficient of hardness (r = 0.84) and WBSF (r = 0.79) parameters with the phenylalanine Raman signal at 1,003 cm^-1, suggests that the content of this amino acid could explain the differences between samples. Conclusion: Raman spectroscopy with 785 nm laser excitation is a suitable and accurate technique to identify beef with different quality attributes.

• Journal of Dental Anesthesia and Pain Medicine
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• v.23 no.4
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• pp.213-220
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• 2023

Background: Third molar extraction is the most commonly performed minor oral surgical procedure in outpatient settings and requires regional anesthesia for pain control. Extraction of the maxillary molars commonly requires both posterior superior alveolar nerve block (PSANB) and greater palatine nerve block (GPNB), depending on the nerve innervations of the subject teeth. We aimed to study the effectiveness of PSANB alone in maxillary third molar (MTM) extraction. Methods: A sample size comprising 100 erupted and semi-erupted MTM was selected and subjected to study for extraction. Under strict aseptic conditions, the patients were subjected to the classical local anesthesia technique of PSANB alone with 2% lignocaine hydrochloride and adrenaline 1:80,000. After a latency period of 10 min, objective assessment of the buccal and palatal mucosa was performed. A numerical rating scale and visual analog scale were used. Results: In the post-latency period of 10 min, the depth of anesthesia obtained in our sample on the buccal side extended from the maxillary tuberosity posteriorly to the mesial of the first premolar (15%), second premolar (41%), and first molar (44%). This inferred that anesthesia was effectively high until the first molars and was less effective further anteriorly due to nerve innervation. The depth of anesthesia on the palatal aspect was up to the first molar (33%), second molar (67%), and lateromedially; 6% of the patients received anesthesia only to the alveolar region, whereas 66% received up to 1.5 cm to the mid-palatal raphe. In 5% of the cases, regional anesthesia was re-administered. An additional 1.8 ml PSANB was required in four patients, and another patient was administered a GPNB in addition to the PSANB during the time of extraction and elevation. Conclusion: The results of our study emphasize that PSANB alone is sufficient for the extraction of MTM in most cases, thereby obviating the need for poorly tolerated palatal injections.

• Steel and Composite Structures
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• v.46 no.3
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• pp.319-334
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• 2023

Localizing damages is an essential task to monitor the health of the structures since they may not be able to operate anymore. Among the damage detection techniques, non-destructive methods are considerably more preferred than destructive methods since damage can be located without affecting the structural integrity. However, these methods have several drawbacks in terms of detecting abilities, time consumption, cost, and hardware or software requirements. Employing artificial intelligence techniques could overcome such issues and could provide a powerful damage detection model if the technique is utilized correctly. In this study, the crack localization in flat and folded plate structures has been conducted by employing a Backpropagated Artificial Neural Network (BPANN). For this purpose, cracks with 18 different dimensions in thin, flat, and folded structures having 15⁰, 30⁰, 45⁰, and 60⁰ folding angle have been modeled and subjected to free vibration analysis by employing the Classical Plate Theory with Finite Element Method. A Four-nodded quadrilateral element having six degrees of freedom has been considered to represent those structures mathematically. The first ten natural frequencies have been obtained regarding healthy and cracked structures. To localize the crack, the ratios of the frequencies of the cracked flat and folded structures to those of healthy ones have been taken into account. Those ratios have been given to BPANN as the input variables, while the crack locations have been considered as the output variables. A total of 500 crack locations have been regarded within the dataset obtained from the results of the free vibration analysis. To build the best intelligent model, a feature search has been conducted for BAPNN regarding activation function, the number of hidden layers, and the number of hidden neurons. Regarding the analysis results, it is concluded that the BPANN is able to localize the cracks with an average accuracy of 95.12%.