• Nuclear Engineering and Technology
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• v.42 no.6
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• pp.704-711
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• 2010

Modal testing requires measuring the vibration of many points, for which an accelerometer, a gab sensor and laser vibrometer are generally used. Conventional modal testing requires mounting of these sensors to all measurement points in order to acquire the signals. However, this can be disadvantageous because it requires considerable measurement time and effort when there are many measurement points. In this paper, we propose a method for modal testing using a camera image. A camera can measure the vibration of many points at the same time. However, this task requires that the measurement points be classified frame by frame. While it is possible to classify the measurement points one by one, this also requires much time. Therefore, we try to classify multiple points using pattern recognition. The feasibility of the proposed method is verified by a beam experiment. The experimental results demonstrate that we can obtain good results.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.55-61
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• 2019

In this paper, if images are acquired in all-time situations through various sensors (EO/IR, SAR, GMTI, LiDAR) used for defense purposes, the images can be analyzed and expressed in augmented reality(AR). Various algorithms are used to process images with augmented reality, and depending on the situation, it is necessary to decide which algorithms to select and use. Through the performance comparison (error rate, processing time, accuracy) of SIFT, SURF, ORB, and BRISK, the representative augmented reality algorithm, it is analyzed and proposed which augmented reality algorithm is effective to use under various situations in the defense field.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.585-586
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• 2019

Recently, the systems for managing the labs provide services that can be managed in real time by using various sensors based on IoT. The system collects sensor data and transmits it to the server, identifies the dangerous situation, and sends operation commands to the devices. These systems have a centralized structure that slows data processing when managing multiple laboratories. To solve this problem, this paper proposes a system that manages laboratories in distributed processing environment to identify and manage risk situations. The sensor module is used to control the laboratory and to automatically identify and respond to the dangerous situation.

• Smart Structures and Systems
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• v.24 no.5
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• pp.617-630
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• 2019

Currently most of the vision-based structural identification research focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation. The structural condition assessment at global level just with the vision-based structural output cannot give a normalized response irrespective of the type and/or load configurations of the vehicles. Combining the vision-based structural input and the structural output from non-contact sensors overcomes the disadvantage given above, while reducing cost, time, labor force including cable wiring work. In conventional traffic monitoring, sometimes traffic closure is essential for bridge structures, which may cause other severe problems such as traffic jams and accidents. In this study, a completely non-contact structural identification system is proposed, and the system mainly targets the identification of bridge unit influence line (UIL) under operational traffic. Both the structural input (vehicle location information) and output (displacement responses) are obtained by only using cameras and computer vision techniques. Multiple cameras are synchronized by audio signal pattern recognition. The proposed system is verified with a laboratory experiment on a scaled bridge model under a small moving truck load and a field application on a footbridge on campus under a moving golf cart load. The UILs are successfully identified in both bridge cases. The pedestrian loads are also estimated with the extracted UIL and the predicted weights of pedestrians are observed to be in acceptable ranges.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.1
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• pp.12-21
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• 2021

For successful automatic target recognition(ATR) with synthetic aperture radar(SAR) imagery, SAR target images of the database should have the identical or highly similar resolution with those collected from SAR sensors. However, it is time-consuming or infeasible to construct the multiple databases with different resolutions depending on the operating SAR system. In this paper, an approach for resolution conversion of SAR target images is proposed based on conditional generative adversarial network(cGAN). First, a number of pairs consisting of SAR target images with two different resolutions are obtained via SAR simulation and then used to train the cGAN model. Finally, the model generates the SAR target image whose resolution is converted from the original one. The similarity analysis is performed to validate reliability of the generated images. The cGAN model is further applied to measured MSTAR SAR target images in order to estimate its potential for real application.

• Journal of Sensor Science and Technology
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• v.30 no.3
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• pp.170-174
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• 2021

As the rising attention to the medical and healthcare issue, Bio-MEMS (Micro electro mechanical systems) platform such as bio sensor, cell culture system, and microfluidics device has been studied extensively. Bio-MEMS platform mostly has high resolution structure made by biocompatible material such as polydimethylsiloxane (PDMS). In addition, three dimension structure has been applied to the bio-MEMS. Lithography can be used to fabricate complex structure by multiple process, however, non-rectangular cross section can be implemented by introducing optical apparatus to lithography technic. X-ray lithography can be used even for sub-micron scale. Here in, we demonstrated lines with round shape cross section using the tilted gold absorber which was deposited on the oblique structure as the X-ray mask. This structure was used as a mold for PDMS. Molded PDMS was applied to the cell culture platform. Moreover, molded PDMS was bonded to flat PDMS to utilize to the sub-micro channel. This work has potential to the large area bio-MEMS.

• Journal of Sensor Science and Technology
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• v.30 no.3
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• pp.148-153
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• 2021

During the manufacture of a ZnS lens with excellent transmittance in the mid-infrared region (3-5 ㎛) by the hot-press process, a single-layer sintering method is used in which one lens is manufactured in one process. Additional research is required to improve this single-layer sintering method because of its low manufacturing efficiency. To solve this problem, the variation in optical properties of ZnS lenses with change in sintering temperature was investigated by introducing a Stack sintering method that can sinter multiple lenses simultaneously. A carbon paper was placed between the molded lenses and sintered into five layers. The average permeability of 67% at medium infrared wavelengths of 3-5 ㎛ was excellent under the following sintering conditions: pressure of 50 MPa and temperature of 850℃. This value is 1% less than the average permeability in the case of single-layer sintering of the ZnS lens. It was confirmed that the stack sintering method developed in this study can be used to manufacture a large number of lenses with excellent characteristics in a single process.

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.13-22
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• 2020

This paper presents an adaptive feedback based actuator fault detection and tolerant control algorithms for longitudinal functional safety of autonomous driving. In order to ensure the functional safety of autonomous vehicles, fault detection and tolerant control algorithms are needed for sensors and actuators used for autonomous driving. In this study, adaptive feedback control algorithm to compute the longitudinal acceleration for autonomous driving has been developed based on relationship function using states. The relationship function has been designed using feedback gains and error states for adaptation rule design. The coefficients in the relationship function have been estimated using recursive least square with multiple forgetting factors. The MIT rule has been adopted to design the adaptation rule for feedback gains online. The stability analysis has been conducted based on Lyapunov direct method. The longitudinal acceleration computed by adaptive control algorithm has been compared to the actual acceleration for fault detection of actuators used for longitudinal autonomous driving.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.12
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• pp.987-995
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• 2020

Accurate alignment between high-performance payloads and attitude control sensors is essential factor to guarantee accurate attitude orientation and high pointing stability of the satellite. Space craft developers often use theodolite measurement system for satellite alignment during ground AIT(Assembly Integration and Test) phase. When measuring theodolite, errors may occur due to line of sight error, tilting axis error, vertical index error, and vertical axis error. In addition, errors that can occur during alignment measurements with multiple theodolites are analyzed through the alignment cube measurements test. Based on the alignment cube measurements test, a technical method that can improve the alignment measurement accuracy was suggested and it's measurements results satisfied the satellite design requirements.

• 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.