• Journal of the Korean Magnetic Resonance Society
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• v.24 no.4
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• pp.104-116
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• 2020

Fipronil, the phenylpyrazole insecticide, is effective and used in various fields. Especially, fipronil was reliable because it was known to be specific on invertebrate animals than vertebrate animals including mammals. However, fipronil had potential risks that affect vertebrate animals as it blocks the gamma-aminobutyric acid (GABA) receptors that also exists in vertebrates as well as invertebrates. Therefore, it was necessary that harmful effects of fipronil on vertebrates are clarified. For this purpose, the zebrafish (Danio rerio) were used on behalf of vertebrate animals in present study. The zebrafish were exposed to 5 ㎍/L, 25 ㎍/L, and 50 ㎍/L of fipronil during 12, 24 and 72 hours. To closely observe toxic process, 12 hours and 24 hours of additional time point were set in the exposure test. Nuclear magnetic resonance (NMR)-based metabolomics is an approach to detect metabolic changes in organism resulted from external stimuli. In this study, NMR-based metabolomics showed the metabolic changes in zebrafish caused by fipronil exposure. Metabolic analysis revealed that fipronil interfered with energy metabolism and decreased the antioxidant ability in zebrafish. Antioxidant ability decline was remarkable at high exposure concentration. In addition, metabolic analysis results over time suggested that reactions for alleviating the excessive nerve excitation occurred in zebrafish after fipronil exposure. Through this study, it was elucidated that the adverse effects of fipronil on vertebrate animals are evident. The risk of fipronil on vertebrates can be no longer ignored. Moreover, this study has a meaning of practically necessary research for organism by examining the effects of fipronil at low concentrations existed in real environment.

• Wind and Structures
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• v.33 no.6
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• pp.463-470
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• 2021

This study investigates the aerodynamic characteristics of NACA series airfoil by altering the trailing edge in the form of extended and serrated sections. This contemporary advent examined NACA 0020 airfoil experimentally at the angle of attack ranging from 0° to 45° and for the Reynolds number of 2.46 × 105. To figure out the flow behaviour, the standard average pressure distribution over the airfoil surface is estimated with 50 pressure taps. The time series surface pressure is recorded for 700 Hz of sampling frequency. The extended trailing edge of 0.1 c, 0.2 c and 0.3 c are attached to the base airfoil. Further, the triangular serration is introduced with the base length of 2 cm, 4 cm and 6 cm. Each base length with three different amplitudes of 0.1 c, 0.2 c and 0.3 c were designed and equipped with the baseline case at the trailing edge and tested. The aerodynamic force coefficient, as well as pressure coefficient are presented. The obtained data advises that modification in the trailing edge will reflect the aerodynamic characteristics and the flow behaviour over the section of a wing. Resultantly, the extended trailing edge as a thin elongated surface attached to a base airfoil without revising the main airfoil favors good lift increment. The serrated trailing edge acts as a flow control device by altering the flow pattern results to delay the stall phenomenon. Besides it, improves lift co-efficient with less amount of additional drag. This extended and serrated trailing edge approach can support for designing the future smart airfoil.

• Advances in nano research
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• v.12 no.5
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• pp.529-547
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• 2022

Graphene is one of the strongest, stiffest, and lightest nanoscale materials known to date, making it a potentially viable and attractive candidate for developing lightweight structural composites to prevent high-velocity ballistic impact, as commonly encountered in defense and space sectors. In-plane twist in bilayer graphene has recently revealed unprecedented electronic properties like superconductivity, which has now started attracting the attention for other multi-physical properties of such twisted structures. For example, the latest studies show that twisting can enhance the strength and stiffness of graphene by many folds, which in turn creates a strong rationale for their prospective exploitation in high-velocity impact. The present article investigates the ballistic performance of twisted bilayer graphene (tBLG) nanostructures. We have employed molecular dynamics (MD) simulations, augmented further by coupling gaussian process-based machine learning, for the nanoscale characterization of various tBLG structures with varying relative rotation angle (RRA). Spherical diamond impactors (with a diameter of 25Å) are enforced with high initial velocity (V_i) in the range of 1 km/s to 6.5 km/s to observe the ballistic performance of tBLG nanostructures. The specific penetration energy (E_p^*) of the impacted nanostructures and residual velocity (V_r) of the impactor are considered as the quantities of interest, wherein the effect of stochastic system parameters is computationally captured based on an efficient Gaussian process regression (GPR) based Monte Carlo simulation approach. A data-driven sensitivity analysis is carried out to quantify the relative importance of different critical system parameters. As an integral part of this study, we have deterministically investigated the resonant behaviour of graphene nanostructures, wherein the high-velocity impact is used as the initial actuation mechanism. The comprehensive dynamic investigation of bilayer graphene under the ballistic impact, as presented in this paper including the effect of twisting and random disorder for their prospective exploitation, would lead to the development of improved impact-resistant lightweight materials.

• Journal of Animal Science and Technology
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• v.63 no.6
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• pp.1453-1463
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• 2021

Feeding is the most important behavior that represents the health and welfare of weanling pigs. The early detection of feed refusal is crucial for the control of disease in the initial stages and the detection of empty feeders for adding feed in a timely manner. This paper proposes a real-time technique for the detection and recognition of small pigs using a deep-leaning-based method. The proposed model focuses on detecting pigs on a feeder in a feeding position. Conventional methods detect pigs and then classify them into different behavior gestures. In contrast, in the proposed method, these two tasks are combined into a single process to detect only feeding behavior to increase the speed of detection. Considering the significant differences between pig behaviors at different sizes, adaptive adjustments are introduced into a you-only-look-once (YOLO) model, including an angle optimization strategy between the head and body for detecting a head in a feeder. According to experimental results, this method can detect the feeding behavior of pigs and screen non-feeding positions with 95.66%, 94.22%, and 96.56% average precision (AP) at an intersection over union (IoU) threshold of 0.5 for YOLOv3, YOLOv4, and an additional layer and with the proposed activation function, respectively. Drinking behavior was detected with 86.86%, 89.16%, and 86.41% AP at a 0.5 IoU threshold for YOLOv3, YOLOv4, and the proposed activation function, respectively. In terms of detection and classification, the results of our study demonstrate that the proposed method yields higher precision and recall compared to conventional methods.

• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.17-27
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• 2022

In this study, a deep learning-based network that can predict the aerodynamic characteristics of airfoils was designed, and the feasibility of the proposed network was confirmed by applying aerodynamic data generated by Xfoil. The prediction of aerodynamic characteristics according to the variation of airfoil thickness was performed. Considering the angle of attack, the coordinate data of an airfoil is converted into image data using signed distance function. Additionally, the distribution of the pressure coefficient on airfoil is expressed as reduced data via proper orthogonal decomposition, and it was used as the output of the proposed network. The test data were constructed to evaluate the interpolation and extrapolation performance of the proposed network. As a result, the coefficients of determination of the lift coefficient and moment coefficient were confirmed, and it was found that the proposed network shows benign performance for the interpolation test data, when compared to that of the extrapolation test data.

• The Korean Journal of Pain
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• v.36 no.1
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• pp.98-105
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• 2023

Background: Ultrasound-guided first sacral transforaminal epidural steroid injection (S1 TFESI) is a useful and easily applicable alternative to fluoroscopy or computed tomography (CT) in lumbosacral radiculopathy. When a needle approach is used, poor visualization of the needle tip reduces the accuracy of the procedure, increasing its difficulty. This study aimed to improve ultrasound-guided S1 TFESI by evaluating radiological S1 posterior foramen data obtained using three-dimensional CT (3D-CT). Methods: Axial 3D-CT images of the pelvis were retrospectively analyzed. The radiological measurements obtained from the images included 1st posterior sacral foramen depth (S1D, mm), 1st posterior sacral foramen width (S1W, mm), the angle of the 1st posterior sacral foramen (S1A, °), and 1st posterior sacral foramen distance (S1ds, mm). The relationship between the demographic factors and measured values were then analyzed. Results: A total of 632 patients (287 male and 345 female) were examined. The mean S1D values for males and females were 11.9 ± 1.9 mm and 10.6 ± 1.8 mm, respectively (P < 0.001); the mean S1A 28.2 ± 4.8° and 30.1 ± 4.9°, respectively (P < 0.001); and the mean S1ds, 24.1 ± 2.9 mm and 22.9 ± 2.6 mm, respectively (P < 0.001); however, the mean S1W values were not significantly different. Height was the only significant predictor of S1D (β = 0.318, P = 0.004). Conclusions: Ultrasound-guided S1 TFESI performance and safety may be improved with adjustment of needle insertion depth congruent with the patient's height.

• Journal of Korean Neurosurgical Society
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• v.66 no.1
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• pp.33-43
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• 2023

Objective : To compare the outcomes of anterior lumbar interbody fusion (ALIF), oblique lumbar interbody fusion (OLIF), and transforaminal lumbar interbody fusion (TLIF) in terms of global sagittal alignment. Methods : From January 2007 to December 2019, 141 adult patients who underwent multilevel interbody fusion for lumbar degenerative disorders were enrolled. Regarding the approach, patients were divided into the ALIF (n=23), OLIF (n=60), and TLIF (n=58) groups. Outcomes, including local radiographic parameters and global sagittal alignment, were then compared between the treatment groups. Results : Regarding local radiographic parameters, ALIF and OLIF were superior to TLIF in terms of the change in the anterior disc height (7.6±4.5 mm vs. 6.9±3.2 mm vs. 4.7±2.9 mm, p<0.001), disc angle (-10.0°±6.3° vs. -9.2°±5.2° vs. -5.1°±5.1°, p<0.001), and fused segment lordosis (-14.5°±11.3° vs. -13.8°±7.5° vs. -7.4°±9.1°, p<0.001). However, regarding global sagittal alignment, postoperative lumbar lordosis (-42.5°±9.6° vs. -44.4°±11.6° vs. -40.6°±12.3°, p=0.210), pelvic incidence-lumbar lordosis mismatch (7.9°±11.3° vs. 6.7°±11.6° vs. 11.5°±13.0°, p=0.089), and the sagittal vertical axis (24.3±28.5 mm vs. 24.5±34.0 mm vs. 25.2±36.6 mm, p=0.990) did not differ between the groups. Conclusion : Although the anterior approaches were superior in terms of local radiographic parameters, TLIF achieved adequate global sagittal alignment, comparable to the anterior approaches.

• Journal of the Korean Geotechnical Society
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• v.24 no.11
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• pp.17-24
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• 2008

It is known that scour at bridge piers is one of the leading causes of bridge failure. However, the mechanism of flow around a pier structure is so complicated that it is difficult to establish a general empirical model to provide accurate estimation for scour. Especially, each of the proposed empirical formula yields good results for a particular data set but can't show reliable predictability for various scouring data set. In this study, an alternative approach, that is, artificial neural networks (ANN), is proposed to estimate the local scour depth with numerous field data base. The local scour depth was modeled as a function of seven variables; pier shape, pier width, pier length, skew angle, stream velocity, water depth, $D_{50}$. 426 field data were used for the training and testing of ANN model. The predicted results showed that the neural network could provide a better alternative to the empirical equations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.476-477
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• 2022

This study deals with rotation, which is one of the expression methods of motion used in the 3D development environment. Euler angle is a rotation method introduced by Leonhard Euler to display objects in three-dimensional space. Although three angles can handle all rotations in a three dimensional coordinate space, there are serious errors in this approach. If you rotate an object with Euler angles, you will face the problem of gimbal locks that cannot rotate under certain circumstances. In contrast to this, the method to rotate an object without a gimbal lock is the quaternion rotation with quaternion. Rather than a detailed mathematical proof of quaternion, it introduces what concept is used in the current 3D development environment, and applies it to camera rotation control to implement a rotating camera without a gimbal lock.

• Journal of the Korea Institute of Building Construction
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• v.23 no.5
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• pp.629-638
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• 2023

This study introduces an innovative approach to monitor the whereabouts of workers within indoor construction settings. While traditional modalities such as GPS and NTRIP have demonstrated efficacy for outdoor localizations, their precision dwindles in indoor environments. In response, this research advocates for the adoption of Aruco markers. Leveraging computer vision technology, these markers facilitate the quantification of the distance between a worker and the marker, subsequently pinpointing the worker's instantaneous location with heightened accuracy. The methodology's efficacy was rigorously evaluated in a real-world construction scenario. Parameters including system stability, the influence of lighting conditions, the extremity of measurable distances, and the breadth of recognition angles were methodically appraised. System stability was ascertained by maneuvering the camera at a uniform velocity, gauging its marker recognition prowess. The impact of varying luminosity on marker discernibility was scrutinized by modulating the ambient lighting. Furthermore, the camera's spatial movement ascertained both the upper threshold of distance until marker recognition waned and the maximal angle at which markers remained discernible.