• International journal of advanced smart convergence
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• v.8 no.2
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• pp.211-217
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• 2019

This study is designed to reduce worker fatigue, improve efficiency and provide a functional working environment based on previous studies that pain occurs in the shoulder area, especially the upper trapezius muscle, when the keyboard height is not appropriate. In this study, the height of the keyboard is four, the height of the elbow and desk is the same height, the height of the desk is 3cm lower than the elbow, the height of the desk is 6cm high, and the height is 9cm high. When working on the keyboard, the wrist and forerunner were organized into four groups of 10 people so that the height was different for each group. When the height of the keyboard is given in various ways compared to the height of the elbow of the subject, it is verified whether there is a difference in the RMS (Root Mean Square) of the upper trapezius muscle. The results of this study showed that the muscle activity of the upper trapezius muscle cap was significant only in the left and right keyboard height -4cm, 0cm, +4cm, +8cm group, but the difference in muscle activity was not significant in the rest group. The first study will require a study of the control of the factors affecting the tension of the subjects, the measurement of muscle activity against various muscles, and whether the length of the shoulder and fingertips of the subject affect muscle activity according to the keyboard type.

• International journal of advanced smart convergence
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• v.8 no.1
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• pp.184-195
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• 2019

This study investigates the hair restoration efficacy of selected radish saponin extracts on nude mice. Nude mice genetically predisposed to pattern balding were used in this study. Our study revealed the underlying mechanism of stimulating hair growth in athymic nude mice by repair the nu/nu follicular keratin differentiation defect. Thus, the topical application of radish saponin may represent a novel strategy for the management and therapy of certain forms of alopecia. The term of hair density of PEE treated nude mice were significantly increase as compared with of control nude mice. Histological observation of skin sample showed no hair follicle or only distorted hair follicles were observed in the control samples, in contrast, by the PEE treatment groups showed a fully formed and increased the number of hair follicles up to three times higher than that of control group in terms of the number of hair follicles in nude mouse skin.PEE treated mice the number of BrdU-labeled keratinocytes per anagen follicle increased significantly, especially in the follicular bulbs and outer root sheath compared with the control mice. Moreover, PEE-treated nude mice also exhibited a significant increase in the number of BrdU-labeled epidermal keratinocyte proliferation.

• Smart Structures and Systems
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• v.24 no.1
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• pp.95-110
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• 2019

The semi-active impact damper (SAID) is proposed to improve the damping efficiency of traditional passive impact dampers. In order to investigate its damping mechanism and vibration control effects on realistic engineering structures, a 20-story nonlinear benchmark building is used as the main structure. The studies on system parameters, including the mass ratio, damping ratio, rigid coefficient, and the intensity of excitation are carried out, and their effects both on linear and nonlinear indexes are evaluated. The damping mechanism is herein further investigated and some suggestions for the design in high-rise buildings are also proposed. To validate the superiority of SAID, an optimal passive particle impact damper ($PID_{opt}$) is also investigated as a control group, in which the parameters of the SAID remain the same, and the optimal parameters of the $PID_{opt}$ are designed by differential evolution algorithm based on a reduced-order model. The numerical simulation shows that the SAID has better control effects than that of the optimized passive particle impact damper, not only for linear indexes (e.g., root mean square response), but also for nonlinear indexes (e.g., component energy consumption and hinge joint curvature).

• Smart Structures and Systems
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• v.24 no.4
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• pp.507-524
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• 2019

A Bayesian dynamic linear model (BDLM) is presented for a data-driven analysis for response prediction and load effect separation of a revolving auditorium structure, where the main loads are self-weight and dead loads, temperature load, and audience load. Analyses are carried out based on the long-term monitoring data for static strains on several key members of the structure. Three improvements are introduced to the ordinary regression BDLM, which are a classificatory regression term to address the temporary audience load effect, improved inference for the variance of observation noise to be updated continuously, and component discount factors for effective load effect separation. The effects of those improvements are evaluated regarding the root mean square errors, standard deviations, and 95% confidence intervals of the predictions. Bayes factors are used for evaluating the probability distributions of the predictions, which are essential to structural condition assessments, such as outlier identification and reliability analysis. The performance of the present BDLM has been successfully verified based on the simulated data and the real data obtained from the structural health monitoring system installed on the revolving structure.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.57-67
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• 2021

An earthquake occurred on 17 November 2017 in Pohang, South Korea with a strength of 5.4 Mw. This is the second strongest earthquake recorded by local authorities since the equipment was first installed. In order to improve understanding of earthquakes and surface deformation, many studies have been conducted according to these phenomena. In this research, we will estimate the surface deformation using the Okada model equation. The SAR images of three satellites with different wavelengths (ALOS-2, Cosmo SkyMed and Sentinel-1) were used to produce the interferogram pairs. The interferogram is used as a reference for surface deformation changes by using Okada to determine the source of surface deformation that occurs during an earthquake. The Non-linear optimization (Levemberg-Marquadrt algorithm) and Monte Carlo restart was applied to optimize the fault parameter on modeling process. Based on the modeling results of each satellite data, the fault geometry is ~6 km length, ~2 km width and ~5 km depth. The root mean square error values in the surface deformation model results for Sentinel, CSK and ALOS are 0.37 cm, 0.79 cm and 1.47 cm, respectively. Furthermore, the results of this modeling can be used as learning material in understanding about seismic activity to minimize the impacts that arise in the future.

• Smart Structures and Systems
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• v.28 no.6
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• pp.761-777
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• 2021

This study presents a numerical investigation on the sensitivity of electromechanical (EM) impedance responses to inner damaged concrete of a prestressed anchorage zone. Firstly, the Ottosen yield criterion is selected to simulate the plasticity behavior of the concrete anchorage zone under the compressive loading. Secondly, several overloading cases are selected to analyze inner damage formations in the concrete of the anchorage zone. Using a finite element (FE) model of the anchorage zone, the relationship between applied forces and stresses is analyzed to illustrate inner plasticity regions in concrete induced by the overloading. Thirdly, EM impedance responses of surface-mounted PZT (lead-zirconate-titanate) sensors are numerically acquired before and after concrete damage occurrence in the anchorage zone. The variation of impedance responses is estimated using the RMSD (root-mean-square-deviation) damage metric to quantify the sensitivity of the signals to inner damaged concrete. Lastly, a novel PZT skin, which can measure impedance signatures in predetermined frequency ranges, is designed for the anchorage zone to sensitively monitor the EM impedance signals of the inner damaged concrete. The feasibility of the proposed method is numerically evaluated for a series of damage cases of the anchorage zone. The results reveal that the proposed impedance-based method is promising for monitoring inner damaged concrete in anchorage zones.

• Smart Structures and Systems
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• v.29 no.4
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• pp.523-533
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• 2022

A novel metaheuristic search method, namely black widow optimization (BWO) is employed to increase the accuracy of slope stability analysis. The BWO is a recently-developed optimizer that supervises the training of an artificial neural network (ANN) for predicting the factor of safety (FOS) of a single-layer cohesive soil slope. The designed slope bears a loaded foundation in different distances from the crest. A sensitivity analysis is conducted based on the number of active individuals in the BWO algorithm, and it was shown that the best performance is acquired for the population size of 40. Evaluation of the results revealed that the capability of the ANN was significantly enhanced by applying the BWO. In this sense, the learning root mean square error fell down by 23.34%. Also, the correlation between the testing data rose from 0.9573 to 0.9737. Therefore, the postposed BWO-ANN can be promisingly used for the early prediction of FOS in real-world projects.

• Smart Structures and Systems
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• v.29 no.4
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• pp.641-652
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• 2022

High-rise structures prone to large vibrations under the action of strong winds, resulting in fatigue damage of the structural components and the foundation. A novel compound damping cable system (CDCS) is proposed to suppress the excessive vibrations. CDCS uses tailored double cable system with increased tensile stiffness as the connecting device, and makes use of the relative motion between the high-rise structure and the ground to drive the damper to move back-and-forth, dissipating the vibration mechanical energy of the high-rise structure so as to decaying the excessive vibration. Firstly, a third-order differential equation for the free vibration of high-rise structure with CDCS is established, and its closed form solution is obtained by the root formulas of cubic equation (Shengjin's formulas). Secondly, the analytical solution is validated by a laboratory model experiment. Thirdly, parametric analysis is conducted to investigate how the parameters affect the vibration control performance. Finally, the dynamic responses of the high-rise structure with CDCS under harmonic and stochastic excitations are calculated and its vibration mitigation performance is further evaluated. The results show that the CDCS can provide a large equivalent additional damping ratio for the vibrating structures, thus suppressing the excessive vibration effectively. It is anticipated that the CDCS can be used as a good alternative energy dissipation system for vibration control of high-rise structures.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.211-220
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• 2023

Surface electromyography (sEMG) is a noninvasive method used to capture electrically muscle activity, which can be easily measured even during exercise. The basic unit of muscle activity is the motor unit, and because an sEMG signal is a superposition of motor unit action potentials, analysis of muscle activity using sEMG should ideally be done from the perspective of motor unit activity. However, conventional techniques can only evaluate sEMG signals based on abstract signal features, such as root-mean-square (RMS) and mean-power-frequency (MPF), and cannot detect individual motor unit activities from an sEMG signal. On the other hand, needle EMG can only capture the activity of a few local motor units, making it extremely difficult to grasp the activity of the entire muscle. Therefore, in this study, a method to visualize the activities of motor units in a single-channel sEMG signal by relocating wavelet coefficients obtained by redundant discrete wavelet analysis is proposed. The information obtained through this method resides in between the information obtained through needle EMG and the information obtained through sEMG using conventional techniques.

• Smart Structures and Systems
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• v.32 no.2
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• pp.83-99
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• 2023

The temperature prediction approaches of three important locations in an operational longitudinal slab track-bridge structure by using three typical neural network methods based on the field measuring platform of four meteorological factors and internal temperature. The measurement experiment of four meteorological factors (e.g., ambient temperature, solar radiation, wind speed, and humidity) temperature in the three locations of the longitudinal slab and base plate of three important locations (e.g., mid-span, beam end, and Wide-Narrow Joint) were conducted, and then their characteristics were analyzed, respectively. Furthermore, temperature prediction effects of three locations under five various meteorological conditions are tested by using three neural network methods, respectively, including the Artificial Neural Network (ANN), the Long Short-Term Memory (LSTM), and the Convolutional Neural Network (CNN). More importantly, the predicted effects of solar radiation in four meteorological factors could be identified with three indicators (e.g., Root Means Square Error, Mean Absolute Error, Correlation Coefficient of R2). In addition, the LSTM method shows the best performance, while the CNN method has the best prediction effect by only considering a single meteorological factor.