• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.2
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• pp.93-101
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• 2016

This paper presents the results obtained using time-series-based methods for structural damage assessment. The methods are applied to a wind turbine blade structure subjected to fatigue loads. A 9 m CX-100 (carbon experimental 100 kW) blade is harmonically excited at its first natural frequency to introduce a failure mode. Consequently, a through-thickness fatigue crack is visually identified at 8.5 million cycles. The time domain data from the piezoelectric active-sensing techniques are measured during the fatigue loadings and used to detect incipient damage. The damage-sensitive features, such as the first four moments and a normality indicator, are extracted from the time domain data. Time series autoregressive models with exogenous inputs are also implemented. These features could efficiently detect a fatigue crack and are less sensitive to operational variations than the other methods.

• Journal of Communications and Networks
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• v.15 no.3
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• pp.283-291
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• 2013

In this paper, we propose new multiuser detectors (MUDs) based on compressed sensing approaches for the large-scale multiple antenna systems equipped with dozens of low-power antennas. We consider the scenarios where the number of receiver antennas is smaller than the total number of users, but the number of active users is relatively small. This prior information motivates sparsity-embracing MUDs such as sparsity-embracing linear/nonlinear MUDs where the detection of active users and their symbol detection are employed. In addition, sparsity-embracing MUDs with maximum a posteriori probability criterion (MAP-MUDs) are presented. They jointly detect active users and their symbols by exploiting the probability of user activity, and it can be solved efficiently by introducing convex relaxing senses. Furthermore, it is shown that sparsity-embracing MUDs exploiting common users' activity across multiple symbols, i.e., frame-by-frame, can be considered to improve performance. Also, in multiple multiple-input and multiple-output networks with aggressive frequency reuse, we propose the interference cancellation strategy for the proposed sparsity-embracing MUDs. That first cancels out the interference induced by adjacent networks and then recovers the desired users' information by exploiting the low user activity. In simulation studies for binary phase shift keying modulation, numerical evidences establish the effectiveness of our proposed MUDs exploiting low user activity, as compared with the conventional MUD.

• Smart Structures and Systems
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• v.20 no.2
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• pp.175-180
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• 2017

The load-carrying capacity and structural behavior of concrete-filled steel tube (CFST) structures is highly influenced by the grouting compactness in the steel tube. Due to the invisibility of the grout in the steel tube, monitoring of the grouting progress in such a structure is still a challenge. This paper develops an active sensing approach with combined piezoceramic-based smart aggregates (SA) and piezoceramic patches to monitor the grouting compactness of CFST bridge structure. A small-scale steel specimen was designed and fabricated to simulate CFST bridge structure in this research. Before casting, four SAs and two piezoceramic patches were installed in the pre-determined locations of the specimen. In the active sensing approach, selected SAs were utilized as actuators to generate designed stress waves, which were detected by other SAs or piezoceramic patch sensors. Since concrete functions as a wave conduit, the stress wave response can be only detected when the wave path between the actuator and the sensor is filled with concrete. For the sake of monitoring the grouting progress, the steel tube specimen was grouted in four stages, and each stage held three days for cement drying. Experimental results show that the received sensor signals in time domain clearly indicate the change of the signal amplitude before and after the wave path is filled with concrete. Further, a wavelet packet-based energy index matrix (WPEIM) was developed to compute signal energy of the received signals. The computed signal energies of the sensors shown in the WPEIM demonstrate the feasibility of the proposed method in the monitoring of the grouting progress.

• Journal of dental hygiene science
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• v.2 no.2
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• pp.75-83
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• 2002

By extracting the variables related to the work stress generated from dental hygiene, identifying their relationships, this study aims to contribute to academic progress on work stress. The test results of this study are as follows for each hypothesis: 1. Among the work stress sensing factors, role ambiguity showed correlation to the active coping strategy and the passive coping strategy, whereas it did not have any correlation to the evasive reation. However, the physical resource environmental factor showed correlation to the active coping strategy, whereas it did not have any correlation to the other reation. 2. The passive coping strategy, among the work stress coping strategies, influences the role ambiguity, B type, work ambiguity, physical resource environmental factor by about 18.7%. 3. The active coping strategy, among the work stress coping strategies, influences the social support, role ambiguity, work place of health center factor by about 18.9%. 4. The evasive reaction, among the work stress coping strategies, was influenced by only the 36 years old over factor by approximately 4.2%. 5. It was found in all work stress sensing factors that the group with lower social support had a more degree of experiencing stress than the group with higher social support. In case of the behavior pattern, the type A experienced more stress than the type B only in role ambiguity. 6. It was found that the group with the higher social support tended to choose more active coping strategy than the lower social support. In case of behavior pattern, the type B coped more actively than type A in the passive coping strategy.

• Korean Journal of Materials Research
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• v.20 no.5
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• pp.235-240
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• 2010

We investigated the carbon monoxide (CO) gas-sensing properties of nanostructured Al-doped zinc oxide thin films deposited on self-assembled Au nanodots (ZnO/Au thin films). The Al-doped ZnO thin film was deposited onto the structure by rf sputtering, resulting in a gas-sensing element comprising a ZnO-based active layer with an embedded Pt/Ti electrode covered by the self-assembled Au nanodots. Prior to the growth of the active ZnO layer, the Au nanodots were formed via annealing a thin Au layer with a thickness of 2 nm at a moderate temperature of $500^{\circ}C$. It was found that the ZnO/Au nanostructured thin film gas sensors showed a high maximum sensitivity to CO gas at $250^{\circ}C$ and a low CO detection limit of 5 ppm in dry air. Furthermore, the ZnO/Au thin film CO gas sensors exhibited fast response and recovery behaviors. The observed excellent CO gas-sensing properties of the nanostructured ZnO/Au thin films can be ascribed to the Au nanodots, acting as both a nucleation layer for the formation of the ZnO nanostructure and a catalyst in the CO surface reaction. These results suggest that the ZnO thin films deposited on self-assembled Au nanodots are promising for practical high-performance CO gas sensors.

• Smart Structures and Systems
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• v.3 no.2
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• pp.133-146
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• 2007

This paper addresses a new type of broad and stage-based hybrid carbon fiber reinforced polymer (HCFRP) sensor that is suitable for the sensing of infrastructures. The HCFRP sensors, a type of composite sensor, are fabricated with three types of carbon tows of different strength and moduli. For all of the specimens, the active materials are carbon tows by virtue of their electrical conductivity and piezoresistivity. The measurement principles are based on the micro- and macro-fractures of different types of carbon tows. A series of experiments are carried out to investigate the sensing performances of the HCFRP sensors. The main variables include the stack order and volume fractions of different types of carbon tows. It is shown that the change in electrical resistance is in direct proportion to the strain/load in low strain ranges. However, the fractional change in electrical resistance (${\Delta}R/R_0$) is smaller than 2% prior to the macrofractures of carbon tows. In order to improve the resistance changes, measures are taken that can enhance the values of ${\Delta}R/R_0$ by more than 2 times during low strain ranges. In high strain ranges, the electrical resistance changes markedly with strain/load in a step-wise manner due to the gradual ruptures of different types of carbon tows at different strain amplitudes. The values of ${\Delta}R/R_0$ due to the fracture of high modulus carbon tows are larger than 36%. Thus, it is demonstrated that the HCFRP sensors have a broad and stage-based sensing capability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2B
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• pp.107-116
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• 2006

In this paper, we propose a Sensing Resolution-based Grouping(SRG) protocol for wireless sensor networks. SRG is intended for meeting the application's sensing objectives, where sensor nodes are densely deployed and have the determinate accuracy requirement. The primary contribution of this paper is active group header node selection and round-robin procedure, which increase the sensing accuracy and evenly distribute the node energy consumption. The second contribution is use of energy efficient intermediate node selection by considering group size and energy consumption. We present the design principle of SRG and provide simulation results.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.355-372
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• 2021

Recently, high-performance HMDs (Head-Mounted Display) are becoming wireless due to the growth of virtual reality technology. Accordingly, environmental constraints on the hardware usage are reduced, enabling multiple users to experience virtual reality within a single space simultaneously. Existing multi-user virtual reality platforms use the user's location tracking and motion sensing technology based on vision sensors and active markers. However, there is a decrease in immersion due to the problem of overlapping markers or frequent matching errors due to the reflected light. Goal of this study is to develop a multi-user virtual reality moving platform in a single space that can resolve sensing errors and user immersion decrease. In order to achieve this goal hybrid sensing technology was developed, which is the convergence of vision sensor technology for position tracking, IMU (Inertial Measurement Unit) sensor motion capture technology and gesture recognition technology based on smart gloves. In addition, integrated safety operation system was developed which does not decrease the immersion but ensures the safety of the users and supports multimodal feedback. A 6 m×6 m×2.4 m test bed was configured to verify the effectiveness of the multi-user virtual reality moving platform for four users.

• Smart Structures and Systems
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• v.29 no.4
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• pp.589-598
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• 2022

Timber structures are susceptible to structural damages caused by variations in moisture content (MC), inducing severe durability deterioration and safety issues. Therefore, it is of great significance to detect MC levels in timber structures. Compared to current methods for timber MC detection, which are time-consuming and require bulky equipment deployment, Lead Zirconate Titanate (PZT)-enabled stress wave sensing combined with statistic machine learning classification proposed in this paper show the advantage of the portable device and ease of operation. First, stress wave signals from different MC cases are excited and received by PZT sensors through active sensing. Subsequently, two non-baseline features are extracted from these stress wave signals. Finally, these features are fed to a statistic machine learning classifier (i.e., naïve Bayesian classification) to achieve MC detection of timber structures. Numerical simulations validate the feasibility of PZT-enabled sensing to perceive MC variations. Tests referring to five MC cases are conducted to verify the effectiveness of the proposed method. Results present high accuracy for timber MC detection, showing a great potential to conduct rapid and long-term monitoring of the MC level of timber structures in future field applications.

• Journal of KSNVE
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• v.7 no.3
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• pp.427-437
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• 1997

Mean active intensity based active control for the cancellation of radiated noise out of the duct exit is studied. The active intensity control strategy is drerived based on the relation of the exterior sound field out of the duct termination and interior sound field of the duct. One of the characteristics of this control strategy is that the control performance can be maintained regardless of the sensor loction, compared with the conventional local pressure control methods at either interior downstream or exterior field positions. It is also suggested that the digital filtering for the active intensity control can be achieved by time-domain filtered-x LMP (Lest-Mean-Product) adaptive algorithm. Experiments for an open-ended duct are performed to compare the active intensity control performance with conventional pressure control one. Active control experiment of local sound pressure is conducted by widely used filtered-x LMS adaptive Algorithm and active intensity control implementaion uses the derived filter d-x LMP algorithm. It is shown that the exterior sound fileds was much better observable by sensing of the active intensity than by just sound pressure. It is also demonstrated that the global control performance of external field by acoustic intensity is superior to the conventional sound pressure control performance.