• Journal of IKEEE
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• v.22 no.4
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• pp.953-958
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• 2018

In this study, a portable detection system was developed that can detect harmful gas and signals simultaneously in an enclosed space of industrial sites and underground facilities. The developed system is a sensor module for gas detection, a patch type 1 channel small ECG sensor, a module for three-axial acceleration detection sensor, and a system for statistics. In order to verify the performance of the system modules, the digital resolution, signal frequency, output voltage, and ultra-small modules were evaluated. As a result of the performance of the developed system, the digital resolution was 300 (rps) and the signal amplification gain was 500 dB or more, and the ECG module was manufactured with $50mm{\times}10mm{\times}10mm$ to increase patch utilization. It is believed that the product of this research will be valuable if it is used as an IoT-based management system for real-time monitoring of industrial workers.

• Earthquakes and Structures
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• v.20 no.2
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• pp.187-200
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• 2021

The main factor for the amplification of ground motions near the crest or the toe of a slope is the reflection of the incident waves. The effects of the slope topography on the surrounding lands over the crest or at the toe can amplify the seismic responses of buildings. This study investigates the seismic performance of the slope topography and three mid-rise buildings (five, ten, and fifteen-storey) located near the crest and toe of the slope by 3D numerical analysis. The nonlinear model was used to represent the real behavior of building and ground elements. The average results of seven records were used in the investigations. Based on the analysis, the amplification factor of acceleration near the crest and toe of the slope was the most effective at distances of 2.5 and 1.3 times the slope height, respectively. Accordingly, the seismic performance of buildings was studied at a distance equal to the height of the slope from the crest and toe. The seismic response results of buildings showed that the slope topography to have little impact on up to five-storey buildings located near the crest. Taking into account a topography-soil-structure interaction system increases the storey displacement and base shear in the building. Accordingly, in topography-soil-structure interaction analyses, the maximum lateral displacement was increased by 71% and 29% in ten and fifteen-storey buildings, respectively, compare to the soil-structure interaction system. Further, the base shear force was increased by 109% and 78% in these buildings relative to soil-structure interaction analyses.

• Advances in concrete construction
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• v.13 no.5
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• pp.385-394
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• 2022

Recently, an increasing number of cutting-edged studies have shown that designing a smart active control for real-time implementation requires piles of hard-work criteria in the design process, including performance controllers to reduce the tracking errors and tolerance to external interference and measure system disturbed perturbations. This article proposes an effective artificial-intelligence method using these rigorous criteria, which can be translated into general control plants for the management of civil engineering installations. To facilitate the calculation, an efficient solution process based on linear matrix (LMI) inequality has been introduced to verify the relevance of the proposed method, and extensive simulators have been carried out for the numerical constructive model in the seismic stimulation of the active rigidity. Additionally, a fuzzy model of the neural network based system (NN) is developed using an interconnected method for LDI (linear differential) representation determined for arbitrary dynamics. This expression is constructed with a nonlinear sector which converts the nonlinear model into a multiple linear deformation of the linear model and a new state sufficient to guarantee the asymptomatic stability of the Lyapunov function of the linear matrix inequality. In the control design, we incorporated H Infinity optimized development algorithm and performance analysis stability. Finally, there is a numerical practical example with simulations to show the results. The implication results in the RMS response with as well as without tuned mass damper (TMD) of the benchmark building under the external excitation, the El-Centro Earthquake, in which it also showed the simulation using evolved bat algorithmic LMI fuzzy controllers in term of RMS in acceleration and displacement of the building.

• Smart Structures and Systems
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• v.29 no.1
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• pp.77-91
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• 2022

Various monitoring systems have been implemented in civil infrastructure to ensure structural safety and integrity. In long-term monitoring, these systems generate a large amount of data, where anomalies are not unusual and can pose unique challenges for structural health monitoring applications, such as system identification and damage detection. Therefore, developing efficient techniques is quite essential to recognize the anomalies in monitoring data. In this study, several machine learning techniques are explored and implemented to detect and classify various types of data anomalies. A field dataset, which consists of one month long acceleration data obtained from a long-span cable-stayed bridge in China, is employed to examine the machine learning techniques for automated data anomaly detection. These techniques include the statistic-based pattern recognition network, spectrogram-based convolutional neural network, image-based time history convolutional neural network, image-based time-frequency hybrid convolution neural network (GoogLeNet), and proposed ensemble neural network model. The ensemble model deliberately combines different machine learning models to enhance anomaly classification performance. The results show that all these techniques can successfully detect and classify six types of data anomalies (i.e., missing, minor, outlier, square, trend, drift). Moreover, both image-based time history convolutional neural network and GoogLeNet are further investigated for the capability of autonomous online anomaly classification and found to effectively classify anomalies with decent performance. As seen in comparison with accuracy, the proposed ensemble neural network model outperforms the other three machine learning techniques. This study also evaluates the proposed ensemble neural network model to a blind test dataset. As found in the results, this ensemble model is effective for data anomaly detection and applicable for the signal characteristics changing over time.

• Earthquakes and Structures
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• v.24 no.3
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• pp.217-235
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• 2023

Orthogonal pairs of rollers on concave beds (OPRCB) are a low-cost, low-tech rolling-based isolating system, whose high efficiency has been shown in a previous study. However, seismic performance of OPRCB isolators has only been studied in the two-dimensional (2D) state so far. This is while their performance in the three-dimensional (3D) state differs from that of the 2D state, mainly since the vertical accelerations due to rollers' motion in their beds, simultaneously in two orthogonal horizontal directions, are added up and resulting in bigger vertical inertia forces and higher rolling resistance. In this study, first, Lagrange equations were used to derive the governing equations of motion of the OPRCB-isolated buildings in 3D. Then, some regular shear-type OPRCB-isolated buildings were considered subjected to three-component excitations of far- and near-source earthquakes, and their responses were compared to those of their fixed-base counterparts. Finally, the effects of more realistic modeling and analysis were examined by comparing the responses of isolated buildings in 2D and 3D states. Response histories were obtained by the fourth-order Runge-Kutta-Nystrom method, considering the geometrical nonlinearity of isolators. Results reveal that utilizing the OPRCB isolators effectively reduces the acceleration response, however, depending on the system specifications and earthquake characteristics, the maximum responses of isolated buildings in the 3D state can be up to 40% higher than those in the 2D state.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.6
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• pp.424-432
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• 2023

This study deals with the design of a safety device around a leisure boat propeller. The safety device is to be designed to minimize performance degradation attached to propulsors in coastal waters. These devices, important for preventing propeller accidents, negatively gives influence boat performance, especially at higher speeds. In order to minimize the negative effect, the accelerating ducts, normally used in ESDs (Energy Saving Devices) have been chosen as a safety device. The present study aims to design an optimal duct (minimizing negative effect) through the parametric study. Based on the Marine 19A nozzle, the nozzle's thickness and angle were varied to obtain the optimum parameter in the preliminary design by the computational fluid dynamics program Star-CCM+ Ver. 15.02. In the detailed design, a NACA 4-digit Airfoil shape resembling the Marine 19A by modification at the trailing edge was chosen and the optimum shape was chosen according to variation of camber, thickness, and incidence angle for optimization. The optimally designed duct shows a speed decrease of about 10% in the sea trial result, which is much smaller than the normal speed decrease of at least 30%. The present designing method can give wide applications to the leisure boat because the wake is almost the same due to using the outboard propulsor.

• Earthquakes and Structures
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• v.26 no.1
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• pp.17-30
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• 2024

Earthquakes can lead to substantial damage to buildings, with long-period ground motion being particularly destructive. The design of high-performance building structures has become a prominent focus of research. The double-story isolated structure is a novel type of isolated structure developed from base isolated structure. To delve deeper into the building performance of double-story isolated structures, the double-story isolated structure was constructed with the upper isolated layer located in different layers, alongside a base isolated structure for comparative analysis. Nonlinear elastoplastic analyses were conducted on these structures using different ground motion inputs, including ordinary ground motion, near-field impulsive ground motion, and far-field harmonic ground motion. The results demonstrate that the double-story isolated structure can extend the structural period further than the base isolated structure under three types of ground motions. The double-story isolated structure exhibits lower base shear, inter-story displacement, base isolated layer displacement, story shear, and maximum acceleration of the top layer, compared to the base isolated structure. In addition, the double-story isolated structure generates fewer plastic hinges in the frame, causes less damage to the core tube, and experiences smaller overturning moments, demonstrating excellent resistance to overturning and a shock-absorbing effect. As the upper isolated layer is positioned higher, the compressive stress on the isolated bearings of the upper isolated layer in the double-story isolated structure gradually decreases. Moreover, the compressive stress on the isolated bearings of the base isolated layer is lower compared to that of the base isolated structure. However, the shock-absorbing capacity of the double-story isolated structure is significantly increased when the upper isolated layer is located in the middle and lower section. Notably, in regions exposed to long-period ground motion, a double-story isolated structure can experience greater seismic response and reduced shock-absorbing capacity, which may be detrimental to the structure.

• Geomechanics and Engineering
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• v.37 no.5
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• pp.475-498
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• 2024

The prediction of the susceptibility of soil to liquefaction using a limited set of parameters, particularly when dealing with highly unbalanced databases is a challenging problem. The current study focuses on different ensemble learning classification algorithms using highly unbalanced databases of results from in-situ tests; standard penetration test (SPT), shear wave velocity (V_s) test, and cone penetration test (CPT). The input parameters for these datasets consist of earthquake intensity parameters, strong ground motion parameters, and in-situ soil testing parameters. liquefaction index serving as the binary output parameter. After a rigorous comparison with existing literature, extreme gradient boosting (XGBoost), bagging, and random forest (RF) emerge as the most efficient models for liquefaction instance classification across different datasets. Notably, for SPT and V_s-based models, XGBoost exhibits superior performance, followed by Light gradient boosting machine (LightGBM) and Bagging, while for CPT-based models, Bagging ranks highest, followed by Gradient boosting and random forest, with CPT-based models demonstrating lower G_mean(error), rendering them preferable for soil liquefaction susceptibility prediction. Key parameters influencing model performance include internal friction angle of soil (ϕ) and percentage of fines less than 75 µ (F₇₅) for SPT and V_s data and normalized average cone tip resistance (q_c) and peak horizontal ground acceleration (a_max) for CPT data. It was also observed that the addition of V_s measurement to SPT data increased the efficiency of the prediction in comparison to only SPT data. Furthermore, to enhance usability, a graphical user interface (GUI) for seamless classification operations based on provided input parameters was proposed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.6
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• pp.503-512
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• 2018

SAR(Synthetic Aperture Radar) is a technology to acquire images by processing signals obtained from radar, and there is an increasing demand for utilization of high-resolution SAR images. In this paper, for high-speed processing of high-resolution SAR image data, a study for SAR image processing algorithms to achieve optimal performance in multi-core based computer architecture is performed. The performance deterioration due to a large amount of input/output data for high resolution images is reduced by maximizing the memory utilization, and the parallelization ratio of the code is increased by using dynamic scheduling and nested parallelism of OpenMP. As a result, not only the total computation time is reduced, but also the upper bound of parallel performance is increased and the actual parallel performance on a multi-core system with 10 cores is improved by more than 8 times. The result of this study is expected to be used effectively in the development of high-resolution SAR image processing software for multi-core systems with large memory.

• Journal of the Optical Society of Korea
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• v.15 no.2
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• pp.174-181
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• 2011

An airborne sensor is developed for remote sensing on an aerial vehicle (UV). The sensor is an optical payload for an eletro-optical/infrared (EO/IR) dual band camera that combines visible and IR imaging capabilities in a compact and lightweight package. It adopts a Ritchey-Chr$\'{e}$tien telescope for the common front end optics with several relay optics that divide and deliver EO and IR bands to a charge-coupled-device (CCD) and an IR detector, respectively. The EO/IR camera for dual bands is mounted on a two-axis gimbal that provides stabilized imaging and precision pointing in both the along and cross-track directions. We first investigate the mechanical deformations, displacements and stress of the EO/IR camera through finite element analysis (FEA) for five cases: three gravitational effects and two thermal conditions. For investigating gravitational effects, one gravitational acceleration (1 g) is given along each of the +x, +y and +z directions. The two thermal conditions are the overall temperature change to $30^{\circ}C$ from $20^{\circ}C$ and the temperature gradient across the primary mirror pupil from $-5^{\circ}C$ to $+5^{\circ}C$. Optical performance, represented by the modulation transfer function (MTF), is then predicted by integrating the FEA results into optics design/analysis software. This analysis shows the IR channel can sustain imaging performance as good as designed, i.e., MTF 38% at 13 line-pairs-per-mm (lpm), with refocus capability. Similarly, the EO channel can keep the designed performance (MTF 73% at 27.3 lpm) except in the case of the overall temperature change, in which the EO channel experiences slight performance degradation (MTF 16% drop) for $20^{\circ}C$ overall temperate change.