• Journal of Power Electronics
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• v.14 no.4
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• pp.778-787
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• 2014

This study presents an input filter resonance mitigation method for an AC-DC matrix converter. This method combines the advantages of the one-cycle control strategy and the active damping technique. Unnecessary sensors are removed, and system cost is reduced by employing the grid-side input currents as feedback to damp out LC resonance. A model that includes the proposed method and the input filter is established with consideration of the delay caused by the actual controller. A zero-pole map is employed to analyze model stability and to investigate virtual resistor parameter design principles. Based on a double closed-loop control scheme, the one-cycle control strategy does not require any complex modulation index control. Thus, this strategy can be more easily implemented than traditional space vector-based methods. Experimental results demonstrate the veracity of theoretical analysis and the feasibility of the proposed approach.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1717-1725
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• 2008

In this paper, the HILS system is proposed for the AWS ECU of the bi-modal tram. Using the HILS of the AWS ECU, the behavior of the vehicle can be predicted and the reliability of the AWS system also can be verified. The hardware part of the HILS system includes the ECUs, hydraulic systems, steering linkages and sensors of the bi-modal tram. The software part of the HILS system contains the virtual vehicle model and sensor emulation. Driver input conditions, such as vehicle velocity and front steering angle, are provided to the ECUs by the software. The driving simulation of the bi-modal tram is carried out by the HILS. Also, the reliability of the AWS system, including the ECUs and hydraulic systems, is verified.

• Journal of the Semiconductor & Display Technology
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• v.17 no.1
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• pp.88-92
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• 2018

Currently drone industry has become one of the fast growing markets and the technology for unmanned aerial vehicles are expected to continue to develop at a rapid rate. Especially small unmanned aerial vehicle systems have been designed and utilized for the various field with their own specific purposes. In these fields the path planning problem to find the shortest path between two oriented points is important. In this paper we introduce a path planning strategy for an autonomous flight of unmanned aerial vehicles through reinforcement learning with self-positioning technique. We perform Q-learning algorithm, a kind of reinforcement learning algorithm. At the same time, multi sensors of acceleraion sensor, gyro sensor, and magnetic are used to estimate the position. For the functional evaluation, the proposed method was simulated with virtual UAV environment and visualized the results. The flight history was based on a PX4 based drones system equipped with a smartphone.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1452-1455
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• 2021

Recently, point clouds are generated by capturing real space in 3D, and it is actively applied and serviced for performances, exhibitions, education, and training. These point cloud data require post-correction work to be used in virtual environments due to errors caused by the capture environment with sensors and cameras. In this paper, we propose an enhancement technique for 3D point cloud data by applying generative adversarial network(GAN). Thus, we performed an approach to regenerate point clouds as an input of GAN. Through our method presented in this paper, point clouds with a lot of noise is configured in the same shape as the real object and environment, enabling precise interaction with the reconstructed content.

• Journal of Auto-vehicle Safety Association
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• v.14 no.1
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• pp.20-25
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• 2022

This paper presents a development of simulation environment for validation of autonomous driving (AD) algorithm based on Robot Operating System (ROS). ROS is one of the commonly-used frameworks utilized to control autonomous vehicles. For the evaluation of AD algorithm, a 3D autonomous driving simulator has been developed based on LGSVL. Two additional sensors are implemented in the simulation vehicle. First, Lidar sensor is mounted on the ego vehicle for real-time driving environment perception. Second, GPS sensor is equipped to estimate ego vehicle's position. With the vehicle sensor configuration in the simulation, the AD algorithm can predict the local environment and determine control commands with motion planning. The simulation environment has been evaluated with lane changing and keeping scenarios. The simulation results show that the proposed 3D simulator can successfully imitate the operation of a real-world vehicle.

• Journal of the Ergonomics Society of Korea
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• v.14 no.1
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• pp.69-81
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• 1995

Few studies on the biomechanical analysis of hand postures and tool handling tasks exist because of the lack of appropriate measurement techniques for hand force. A measurement system for the finger forces and joint angles for the analysis of manual tool handling tasks was developed in this study. The measurement system consists of a force sensing glove made from twelve Force Sensitive Resistors and an angle-measuring glove (Cyberglove$^{TM}$, Virtual technologies) with eighteem joint angle sensors. A biomechanical model of the hand using the data from the measurement system was also developed. Systems of computerized procedures were implemented inte- grating the hand posture measurement system, biomechanical analysis system, and the task analysis system for manual tool handling tasks. The measurement system was useful in providing the hand force data needed for an existing task analysis system used in CTD risk evaluation. It is expected that the hand posture measurement developed in this study will provide an efficient and cost-effective solution to task analysis of manual tool handling tasks.s.

• ETRI Journal
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• v.44 no.1
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• pp.155-167
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• 2022

The Internet of Things (IoT) is a new paradigm that connects physical and virtual objects from various domains such as home automation, industrial processes, human health, and monitoring. IoT sensors receive information from their environment and forward it to their neighboring nodes. However, the large amounts of exchanged data are vulnerable to attacks that reduce the network performance. Most of the previous security methods for IoT have neglected the energy consumption of IoT, thereby affecting the performance and reducing the network lifetime. This paper presents a new multistep routing protocol based on cellular learning automata. The network lifetime is improved by a performance-based adaptive reward and fine parameters. Nodes can vote on the reliability of their neighbors, achieving network reliability and a reasonable level of security. Overall, the proposed method balances the security and reliability with the energy consumption of the network.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.189-192
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• 2020

가상현실 기술과 IoT 센서와 연결하여 스마트 항만 원격조정하는 프로그램을 설계하였다. 스마트 항만은 항만 자동화 추세에 맞춰진 현대의 항만 시스템이며 그에 따른 기술력 확보가 국가의 경쟁력을 높이는 핵심이 된다. 아두이노로 하드웨어를, 유니티로 소프트웨어 부분을 설계하여 진행했다.

• Journal of Broadcast Engineering
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• v.14 no.6
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• pp.692-702
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• 2009

Real-time virtual studios which could run only on expensive workstations are now available for personal computers thanks to the recent development of graphics hardware. Nevertheless, graphics are rendered off-line in the post production stage in film or TV drama productions, because the graphics' quality is still restricted by the real-time hardware. Software-based camera tracking methods taking only the source video into account take much computation time, and often shows unstable results. To overcome this restriction, we propose a system that stores camera motion data from sensors at shooting time as common virtual studios and uses them in the post production stage, named as POVIS(post virtual imaging system). For seamless registration of graphics onto the camera video, precise zoom lens calibration must precede the post production. A practical method using only two planar patterns is used in this work. We present a method to reduce the camera sensor's error due to the mechanical mismatch, using the Kalman filter. POVIS was successfully used to track the camera in a documentary production and saved much of the processing time, while conventional methods failed due to lack of features to track.

• Spatial Information Research
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• v.21 no.4
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• pp.63-70
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• 2013

With the increasing use of high-performance mobile devices such as smartphones, users have been able to connect to the Internet anywhere, anytime, so that Location Based Services(LBSes) have been popular among the users in order to obtain personalized information associated with their locations. The services have advanced to provide the information realistically and intuitively by adopting Augmented Reality(AR) technology, where the technology utilizes various sensors embedded in the mobile devices. However, the services have inherent problems due to the small screen size of the mobile devices and the complexity of the real world environment. Overlapping contents on a small screen and user's possible movement should be taken into consideration in displaying the icons on objects that block user's environment such as trees and buildings. The problems mainly happen when the services use only user's location and sensor data to calculate the position of the displayed information. In order to solve the problems, this paper proposes a method that applies street data extracted from a digital map. The method uses the street data as well as the location and direction data to determine contents that are placed on both sides of a virtual street which augments the real street. With scrolling the virtual street, which means a virtual movement, some information far away from the location of the user can be identified without user's actual movement. Also the proposed method is implemented for region "Aenigol", and the efficiency and usefulness of the method is verified.