• Journal of IKEEE
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• v.24 no.1
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• pp.59-66
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• 2020

In this study, the characteristics of ITO thin film was investigated to finding a low cost and highly transparent electrodes for display of mobile communication devices. The ITO film was deposited by DC magnetron sputter. The experimental conditions were changed as follows: 1. ambient pressure changed 1 to 3 mTorr with 1mTorr step, 2. bias electric voltage changed with 10V step. The chamber was pumped out by rotary pump until 10^-3Torr then the diffusion pump was used to lower the pressure of 10^-6Torr. The results shows us the film growth was obvious when the bias voltage was larger than 300V, but the overall thickness tendency was existed: the more voltage is the thicker thickness. At 330V bias voltage condition, the deposition rate was the largest and apparent grain was showed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.5
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• pp.713-718
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• 2014

DC urban railway power system consists of DC power network and AC power network. The DC power network supplies electric power to railway vehicles and the AC power network supplies electric power to station electric equipment. Recently, because of power consumption reduction and peak load shaving, intelligent measurement of regenerative energy and renewable energy adapted on DC urban railway is required. For this reason, DC smart metering system for DC power network shall be developed. Therefore, in this paper, DC voltage sensor, current sensor, and DC smart meter were developed and evaluated by performance test. DC voltage sensor was developed for measuring standard voltage range of DC urban railway, and DC current sensor was developed as hall effect split core type in order to install in existing system. DC smart meter possesses function of general intelligent electric power meter, such as measuring electricity and wireless communication etc. And, DC voltage sensor showed average 0.17% of measuring error for 2,000V/50mA, and current sensor showed average 0.21% of measuring error for ${\pm}2,000V/{\pm}4V$ in performance test. Also DC smart meter showed maximum 0.92% of measuring error for output of voltage sensor and current sensor. In similar environment for real DC power network, measuring error rate was under 0.5%. In conclusion, accuracy of DC smart metering system was confirmed by performance test, and more detailed performance will be verified by further real operation DC urban railway line test.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.9-14
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• 2019

In modern society drones are actively utilized in the fields of security, defense, agriculture, communication and so on. Smart technology and artificial intelligence software have been developed with convergence, and the field of use is expected to expand further. On the point of the excellent performance of drones one of the essential technologies is the wireless communication that make the ground facility receive the video streaming obtained by the drones in the air. In the research the concept of communication region is proposed to cover the both the low altitude region for Wi-Fi communication and the high altitude region for LTE communication for the sake of video transmission. Also the hybrid communication structure is designed along the proposed concept and the proposed system is implemented as a communication system in the small size which can be mounted in a small size of drone. It is confirmed that the proposed system contains the effectiveness by showing the ability to successfully transmit HD video streaming in the range of 500 meters and the transfer time between two different communication systems is measured in 200msec by the experiments.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.11
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• pp.851-856
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• 2018

In this study, we analyze the characteristics of wireless power transfer(WPT) based on magnetic resonance in an underwater environment and propose an equivalent model suitable for underwater WPT. The proposed underwater WPT equivalent model is constructed by expanding the free-space WPT T-model reflecting characteristics change according to media. Considering the water salinity, we propose a method to extract the parameters of the proposed model based on the S parameters. To verify the proposed model, a 6.78-MHz underwater WPT system was constructed and compared with the predicted power transfer efficiency of the model. As a result, it was confirmed that the proposed model predicts the variation of characteristics with an average error of less than 3 %.

• Journal of the Microelectronics and Packaging Society
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• v.29 no.1
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• pp.17-33
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• 2022

Ti₃C₂T_X MXene, first reported by Naguib et al. in 2011, has attracted tremendous attention due to its excellent hydrophilicity, electrical conductivity, and mechanical/chemical stability. Since MXene is a two-dimensional material with a thickness of few nanometers, which ensure its flexibility. In last few years, due to these properties many researchers used Ti₃C₂T_X MXene into various fields such as flexible smart sensors, energy harvesting/storage devices, supercapacitors and electromagnetic interference shielding systems. In this review article, we have briefly discussed the various synthesis processes and characteristics of Ti₃C₂T_X MXene. Moreover, we reviewed the latest development of Ti₃C₂T_X MXene as flexible electrode material to be used into different applications.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.25-30
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• 2024

Smart City, a key application area of the AIoT (Artificial Intelligence of Things), provides various services in safety, security, and healthcare sectors through location tracking and location-based services. an IPS (Indoor Positioning System) is required to implement location-based services, and wireless communication technologies such as WiFi, UWB (Ultra-wideband), and BLE (Bluetooth Low Energy) are being applied. BLE, which enables data transmission and reception with low power consumption, can be applied to various IoT devices such as sensors and beacons at a low cost, making it one of the most suitable wireless communication technologies for indoor positioning. BLE utilizes the RSSI (Received Signal Strength Indicator) to estimate the distance, but due to the influence of multipath fading, which causes variations in signal strength, it results in an error of several meters. In this paper, we conducted research on a path loss model that can be applied to BLE IPS for proximity services, and confirmed that optimizing the free space propagation loss coefficient can reduce the distance error between the Tx and Rx devices.

• Science of Emotion and Sensibility
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• v.21 no.4
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• pp.63-76
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• 2018

The purpose of this study was to investigate the effect of contact type textile electrode structure on heart activity signal acquisition for smart healthcare. In this study, we devised six contact type textile electrodes whose electrode size and configuration were manipulated for measuring heart activity signals using computerized embroidery. We detected heart activity signals using a modified lead II and by attaching each textile electrode to the chest band in four healthy male subjects in a standing static posture. We measured the signals four times repeatedly for all types of electrodes. The heart activity signals were sampled at 1 kHz using a BIOPAC ECG100, and the detected original signals were filtered through a band-pass filter. To compare the performance of heart activity signal acquisition among the different structures of the textile electrodes, we conducted a qualitative analysis using signal waveform and size as parameters. In addition, we performed a quantitative analysis by calculating signal power ratio (SPR) of the heart activity signals obtained through each electrode. We analyzed differences in the performance of heart activity signal acquisition of the six electrodes by performing difference and post-hoc tests using nonparametric statistic methods on the calculated SPR. The results showed a significant difference both in terms of qualitative and quantitative aspects of heart activity signals among the tested contact type textile electrodes. Regarding the configurations of the contact type textile electrodes, the three-dimensionally inflated electrode (3DIE) was found to obtain better quality signals than the flat electrode. However, regarding the electrode size, no significant difference was found in performance of heart signal acquisition for the three electrode sizes. These results suggest that the configuration method (flat/3DIE), which is one of the two requirements of a contact type textile electrode structure for heart activity signal acquisition, has a critical effect on the performance of heart activity signal acquisition for wearable healthcare. Based on the results of this study, we plan to develop a smart clothing technology that can monitor high-quality heart activity without time and space constraints by implementing a clothing platform integrated with the textile electrode and developing a performance improvement plan.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.2
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• pp.129-152
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• 2024

In the application of deep learning object detection via CCTV in tunnels, a large number of false positive detections occur due to the poor environmental conditions of tunnels, such as low illumination and severe perspective effect. This problem directly impacts the reliability of the tunnel CCTV-based accident detection system reliant on object detection performance. Hence, it is necessary to reduce the number of false positive detections while also enhancing the number of true positive detections. Based on a deep learning object detection model, this paper proposes a false positive data training method that not only reduces false positives but also improves true positive detection performance through retraining of false positive data. This paper's false positive data training method is based on the following steps: initial training of a training dataset - inference of a validation dataset - correction of false positive data and dataset composition - addition to the training dataset and retraining. In this paper, experiments were conducted to verify the performance of this method. First, the optimal hyperparameters of the deep learning object detection model to be applied in this experiment were determined through previous experiments. Then, in this experiment, training image format was determined, and experiments were conducted sequentially to check the long-term performance improvement through retraining of repeated false detection datasets. As a result, in the first experiment, it was found that the inclusion of the background in the inferred image was more advantageous for object detection performance than the removal of the background excluding the object. In the second experiment, it was found that retraining by accumulating false positives from each level of retraining was more advantageous than retraining independently for each level of retraining in terms of continuous improvement of object detection performance. After retraining the false positive data with the method determined in the two experiments, the car object class showed excellent inference performance with an AP value of 0.95 or higher after the first retraining, and by the fifth retraining, the inference performance was improved by about 1.06 times compared to the initial inference. And the person object class continued to improve its inference performance as retraining progressed, and by the 18th retraining, it showed that it could self-improve its inference performance by more than 2.3 times compared to the initial inference.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.12
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• pp.161-168
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• 2016

Thanks to mass production and provision of smartphones and the HMD (head mounted display), VR (virtual reality) is now being applied to various areas. The VR HMD is the interface equipment which allows users to have realistic experiences through human sensory organs such as vision and auditory sense. Since the majority of VR equipment is operated by the display for both eyes, 360-degree video content and the depth information, the VR mechanism is closely related to human senses, especially vision. Previous studies have focused on how to minimize negative impact such as motion sickness or visual fatigue. Little attention has been paid on research about the visual treatment. Therefore, the focus of this study is to develop technical elements for utilization of vision therapy with the VR HMD and explore possible areas to apply it. To this end, we analyzed the past case studies and technical elements to identify 16 areas for vision therapy. We also developed the optical parameters for utilization of the VR HMD visual targets. The result of this study is expected to be utilized for development of visual targets for vision therapy based on the VR HMD.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.29-43
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• 2019

The calibration of microscopic traffic simulation models has received much attention in the simulation field. Although no standard has been established for it, a genetic algorithm (GA) has been widely employed in recent literature because of its high efficiency to find solutions in such optimization problems. However, the performance still falls short in simulation analyses to support fast decision making. This paper proposes a new calibration procedure using a dual GA and central composite design (CCD) in order to improve the efficiency. The calibration exercise goes through three major sequential steps: (1) experimental design using CCD for a quadratic response surface model (RSM) estimation, (2) 1st GA procedure using the RSM with CCD to find a near-optimal initial population for a next step, and (3) 2nd GA procedure to find a final solution. The proposed method was applied in calibrating the Gipps car-following model with respect to maximizing the likelihood of a spacing distribution between a lead and following vehicle. In order to evaluate the performance of the proposed method, a conventional calibration approach using a single GA was compared under both simulated and real vehicle trajectory data. It was found that the proposed approach enhances the optimization speed by starting to search from an initial population that is closer to the optimum than that of the other approach. This result implies the proposed approach has benefits for a large-scale traffic network simulation analysis. This method can be extended to other optimization tasks using GA in transportation studies.