• Journal of Veterinary Clinics
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• v.40 no.1
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• pp.25-30
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• 2023

The ventral midline approach (VMA) and right flank approach (RFA) are common procedures for the sterilization of bitches. This study compared the different parameters viz. total duration of surgery, recovery time, and length of the incision as well as body temperature, heart rate, respiration rate, and SpO2 in each approach. Twenty (20) bitches were divided randomly for the RFA and VMA. Meloxicam (0.2 mg/kg) was administered subcutaneously half an hour before the induction to provide preemptive analgesia. Diazepam and ketamine were administered intravenously at dose rates of 0.25 mg/kg and 2.5 mg/kg, and 0.17 mg/kg and 3.33 mg/kg, respectively to produce and maintain anesthesia. Each parameter was recorded at the pre-operative, operative and post-operative times. The average duration of surgery and length of incision of RFA (16.1 ± 5.13 min and 2.44 ± 0.83 cm) were significantly lower (p < 0.05) than the VMA (21.3 ± 5.48 min and 3.53 ± 0.7 cm). The operated bitches showed hypothermia (p < 0.05) at 1 hour compared to baseline and 24 hours of surgery. Heart and respiration rates increased significantly (p < 0.05) during traction and severing of ovarian ligaments in bitches within the RFA group, but there was no significant difference within VMA approaches. The sedation score was significantly higher (p < 0.05) at 1 hour after surgery in both approaches. Based on the duration of surgery and length of incision RFA approach was quick and minimal skin wound. Further studies on bitches considering molecular investigations of surgical stress are imperative.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.1
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• pp.39-47
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• 2023

The demand for lightweight and high-strength materials is increasing. However, studies on the bond of concrete and reinforcing bars for high-strength lightweight concrete with a compressive strength of 120 MPa and a unit weight of 20 kN/m³ to structural members are lacking. Therefore, in this paper, 108 specimens of high-strength lightweight concrete with a compressive strength of 120 MPa and a unit weight of about 20 kN/m³ were fabricated, a direct pull-out test was performed, and the bond characteristics were evaluated by comparing the test results with design code. Compared to the decrease in unit weight, the solid bubble shows relatively little reduction in compressive strength and modulus of elasticity. It was f ound to have larger slip and parameter values than concrete with low compressive strength and unit weight.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.374-376
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• 2021

For the diagnosis of cancer-related diseases in clinical practice, pathological examination using biopsy is essential after basic diagnosis using imaging equipment. In order to proceed with such a biopsy, the assistance of an oncologist, clinical pathologist, etc. with specialized knowledge and the minimum required time are essential for confirmation. In recent years, research related to the establishment of a system capable of automatic classification of cancer cells using artificial intelligence is being actively conducted. However, previous studies show limitations in the type and accuracy of cells based on a limited algorithm. In this study, we propose a method to identify a total of 4 cancer cells through a convolutional neural network, a kind of deep learning. The optical images obtained through cell culture were learned through EfficientNet after performing pre-processing such as identification of the location of cells and image segmentation using OpenCV. The model used various hyper parameters based on EfficientNet, and trained InceptionV3 to compare and analyze the performance. As a result, cells were classified with a high accuracy of 96.8%, and this analysis method is expected to be helpful in confirming cancer.

• Steel and Composite Structures
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• v.47 no.6
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• pp.709-728
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• 2023

Experimental and analytical studies were conducted to clarify the influencing mechanisms of the longitudinal reinforcement on performance of axially loaded Reinforced Concrete-Filled Steel Tube (R-CFST) short columns. The longitudinal reinforcement ratio was set as parameter, and 10 R-CFST specimens with five different ratios and three Concrete-Filled Steel Tube (CFST) specimens for comparison were prepared and tested. Based on the test results, the failure modes, load transfer responses, peak load, stiffness, yield to strength ratio, ductility, fracture toughness, composite efficiency and stress state of steel tube were theoretically analyzed. To further examine, analytical investigations were then performed, material model for concrete core was proposed and verified against the test, and thereafter 36 model specimens with four different wall-thickness of steel tube, coupling with nine reinforcement ratios, were simulated. Finally, considering the experimental and analytical results, the prediction equations for ultimate load bearing capacity of R-CFSTs were modified from the equations of CFSTs given in codes, and a new equation which embeds the effect of reinforcement was proposed, and equations were validated against experimental data. The results indicate that longitudinal reinforcement significantly impacts the behavior of R-CFST as steel tube does; the proposed analytical model is effective and reasonable; proper ratios of longitudinal reinforcement enable the R-CFSTs obtain better balance between the performance and the construction cost, and the range for the proper ratios is recommended between 1.0% and 3.0%, regardless of wall-thickness of steel tube; the proposed equation is recommended for more accurate and stable prediction of the strength of R-CFSTs.

• Journal of Korean Tunnelling and Underground Space Association
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• v.12 no.2
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• pp.105-116
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• 2010

The estimation of surface settlement, ground behavior and tunnel displacement are the main factors in urban tunnel design with shallow depth and unconsolidated soil. On deformation analysis of shallow tunnel, it is important to identify possible deformation mechanism of shear bands developing from tunnel shoulder to the ground surface. This paper investigated the effects of key design parameter affecting deformation behavior by numerical analysis using nonlinear model incorporating the reduction of shear stiffness and strength parameters with the increment of the maximum shear strain after the initiation of plastic yielding. Numerical parametric studies are carried out to consider the reduction of shear stiffness and strength parameters, horizontal stress ratio, cohesion and shotcrete thickness.

• Smart Structures and Systems
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• v.31 no.3
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• pp.229-245
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• 2023

The absence of excitation measurements may pose a big challenge in the application of structural damage identification owing to the fact that substantial effort is needed to reconstruct or identify unknown input force. To address this issue, in this paper, an iterative strategy, a synergy of Tikhonov regularization method for force identification and modified Jaya algorithm (M-Jaya) for stiffness parameter identification, is developed for damage identification with partial output-only responses. On the one hand, the probabilistic clustering learning technique and nonlinear updating equation are introduced to improve the performance of standard Jaya algorithm. On the other hand, to deal with the difficulty of selection the appropriate regularization parameters in traditional Tikhonov regularization, an improved L-curve method based on B-spline interpolation function is presented. The applicability and effectiveness of the iterative strategy for simultaneous identification of structural damages and unknown input excitation is validated by numerical simulation on a 21-bar truss structure subjected to ambient excitation under noise free and contaminated measurements cases, as well as a series of experimental tests on a five-floor steel frame structure excited by sinusoidal force. The results from these numerical and experimental studies demonstrate that the proposed identification strategy can accurately and effectively identify damage locations and extents without the requirement of force measurements. The proposed M-Jaya algorithm provides more satisfactory performance than genetic algorithm, Gaussian bare-bones artificial bee colony and Jaya algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2A
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• pp.137-148
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• 2010

This study proposes the optimal ratio of vertical load-carrying capacity (${\beta}$) by investigating structural performances and economic efficiency in the extradosed bridges. Without design standards for the extradosed bridge, Japanese design standards have been used domestically. For the design live load, DL24 is found to be more adequate than DB24. Using the DL24 load, parameter studies are carried out. The parameters are 'main tower height', 'main girder stiffness', and 'cable arrangement'. As a result, it is found that one side cable-stayed extradosed bridges are more economical than double side cable-stayed extradosed bridges. This study also shows that when the ratio of vertical load-carrying capacity(${\beta}$) is 30~50% in the extradosed bridge with the ratio of tower height to main span length 1/6, the extradosed bridge is most economical because of the cable stress less than the allowable stress.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3A
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• pp.523-532
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• 2006

It is thought that the suggestion of efficient and rational design guideline based on the behavior evaluation of bridge structure system the included cross beam is necessary for the construction efficiency of two-I girder steel bridges. Therefore, in this study, the effects of influence parameters are investigated by the behavior analyses of the bridges, in which the influence parameters are location, spacing and rigidity of the cross beam. For this study, the existed two-I girder steel bridges firstly were selected with the model of case study and the FE analyses for some case models were performed to estimate the action of the cross beam in the bridge. From the analyses, it was estimated that if it consider local stress and load distribution of a floor system, shell and solid elements are compatible to modeling of the cross beams. Also, the efficient design guideline for the cross beam of two-I girder steel bridge was suggested from parameter studies used location, spacing and rigidity of the cross beam.

• Smart Structures and Systems
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• v.30 no.5
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• pp.479-500
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• 2022

In this study, a new type of isolation bearing is proposed by combining S-shaped steel plate dampers (SSDs) with a spherical steel bearing, and the seismic control effect of a five-span standard high-speed railway bridge is investigated. The advantages of the proposed S-shaped steel damping friction bearing (SSDFB) are that it cannot only lengthen the structural periods, dissipate the seismic energy, but also prevent bridge unseating due to the restraint effectiveness of SSDs in the large relative displacements between the girders and piers. This study first presents a detailed description and working principle of the SSDFB. Then, mechanical modeling of the SSDFB was derived to fundamentally define its cyclic behavior and obtain key mechanical parameters. The numerical model of the SSDFB's critical component SSD was verified by comparing it with the experimental results. After that, parameter studies of the dimensions and number of SSDs, the friction coefficient, and the gap length of the SSDFBs were conducted. Finally, the longitudinal seismic responses of the bridge with SSDFBs were compared with the bridge with spherical bearing and spherical bearing with strengthened shear keys. The results showed that the SSDFB can not only significantly mitigate the shear force responses and residual displacement in bridge substructures but also can effectively reduce girder displacement and prevent bridge unseating, at a cost of inelastic deformation of the SSDs, which is easy to replace. In conclusion, the SSDFB is expected to be a cost-effective option with both multi-stage energy dissipation and restraint capacity, making it particularly suitable for seismic isolation application to high-speed railway bridges.

• Smart Structures and Systems
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• v.32 no.5
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• pp.319-338
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• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.