• Journal of the Ergonomics Society of Korea
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• v.30 no.1
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• pp.229-235
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• 2011

Objective: Making a new ergonomic interface system based on camera vision system, which helps the handicapped in home environment. Background: Enabling the handicapped to manipulate the consumer electronics by the proposed interface system. Method: A wearable device for capturing the eye image using a near-infrared(NIR) camera and illuminators is proposed for tracking eye gaze position(Heo et al., 2011). A frontal viewing camera is attached to the wearable device, which can recognize the consumer electronics to be controlled(Heo et al., 2011). And the amount of user's eye fatigue can be measured based on eye blink rate, and in case that the user's fatigue exceeds in the predetermined level, the proposed system can automatically change the mode of gaze based interface into that of manual selection. Results: The experimental results showed that the gaze estimation error of the proposed method was 1.98 degrees with the successful recognition of the object by the frontal viewing camera(Heo et al., 2011). Conclusion: We made a new ergonomic interface system based on gaze tracking and object recognition Application: The proposed system can be used for helping the handicapped in home environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1823-1830
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• 2003

This paper presents a multiple face detector based on a robust pupil detection technique. The pupil detector uses active illumination that exploits the retro­reflectivity property of eyes to facilitate detection. The detection range of this method is appropriate for interactive desktop and kiosk applications. Once the location of the pupil candidates are computed, the candidates are filtered and grouped into pairs that correspond to faces using heuristic rules. To demonstrate the robustness of the face detection technique, a dual mode face tracker was developed, which is initialized with the most salient detected face. Recursive estimators are used to guarantee the stability of the process and combine the measurements from the multi­face detector and a feature correlation tracker. The estimated position of the face is used to control a pan­tilt servo mechanism in real­time, that moves the camera to keep the tracked face always centered in the image.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.640-647
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• 2007

This paper presents a joint controller for a humanoid robot based on genetic algorithm. h humanoid robot has basically instability during walking because it isn't fixed on the ground. Moreover nonlinearities of the joints increase its instability. If one of them isn't satisfied, the robot may fall down at the ground during walking. To attack one of those problems, joint controller is proposed. It can perform tracking control preciously and reduce the effect of nonlinearities by gear, limitation of the input voltage, coulomb friction and so on. This controller is based on fuzzy-sliding mode controller (FSMC) and compensator and control gains are searched by a proposed genetic algorithm. It can reduce the effect by nonlinearities. Also, to improve the tracking performance, the proposed controller has motion controller. From the given controller, a humanoid robot can moved more preciously. Here, all the processes are investigated through simulations and it is verified experimentally in a real joint system for a humanoid robot.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.121-129
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• 2023

In this paper, we developed a traffic signal control system for emergency situations that can minimize loss of property and life by actively controlling traffic signals in a certain section in response to emergency situations. When the emergency vehicle terminal transmits an emergency signal including identification information and GPS information, the surrounding image is obtained from the camera, and the object is analyzed based on deep learning to output object information having information such as the location, type, and size of the object. After generating information tracking this object and detecting the signal system, the signal system is switched to emergency mode to identify and track the emergency vehicle based on the received GPS information, and to transmit emergency control signals based on the emergency vehicle's traveling route. It is a system that can be transmitted to a signal controller. This system prevents the emergency vehicle from being blocked by an emergency control signal that is applied first according to an emergency signal, thereby minimizing loss of life and property due to traffic obstacles.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.103-112
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• 2010

In this paper, we propose a coarse and fine frequency synchronization method which is suitable for the 3GPP(3rd Generation Partnership Project) LTE(Long Term Evolution) FDD(Frequency Division Duplexing) / TDD(Time Division Duplexing) dual mode system. In general, PSS(Primary Synchronization Signal) correlation based estimation method and CP(Cyclic Prefix) correlation based tracking loop are applied for coarse and fine frequency synchronization in 3GPP LTE OFDMA(Orthogonal Frequency Division Multiple Access) system, respectively. However, the conventional coarse frequency synchronization method has performance degradation caused by fading channel and squaring loss. Also, the conventional fine frequency synchronization method cannot guarantee stable operation in TDD mode because of signal power difference between uplink and downlink subframe. Therefore, in this paper, we propose enhanced coarse and fine frequency synchronization methods which can estimate more accurately in multi-path fading channel and high speed channel environments and has stable operation for TDD frame structure, respectively. By computer simulation, we show that the proposed methods outperform the conventional methods, and verify that the proposed frequency synchronization method can guarantee stable operation in 3GPP LTE FDD/TDD dual mode downlink receiver.

• Journal of Advanced Navigation Technology
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• v.10 no.2
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• pp.173-180
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• 2006

An airborne radar is an essential aviation electronic system of the aircraft to perform various missions in all weather environments. This paper presents the design, development, and test results of the multi-mode pulsed Doppler radar system test model for helicopter-borne flight test. This radar system consists of 4 LRU units, which include ANTU(Antenna Unit), TRU(Tx Rx Unit), RSDU(Radar Signal & Data Processing Unit) and DISU(Display Unit). The developed technologies include the TACCAR processor, planar array antenna, TWTA transmitter, coherent I/Q detector, digital pulse compression, DSP based Doppler FFT filtering, adaptive CFAR, IMU, and tracking capability. The design performance of the developed radar system is verified through various helicopter-borne field tests including MTD (Moving Target Detector) capability for the Doppler compensation due to the moving platform motion.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.763-770
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• 2017

A radome mounted on the front of an aircraft can cause refraction errors for various reasons that occur during maneuver in seeking and tracking a target. This refraction error means that the microwave seeker is detecting apparent target. An Interactive Multiple Model (IMM) algorithm is applied to estimate radome slope mounted on an aircraft in 3D space. However, even though the parameter of uncertain system model such as radome slope can be estimated, the estimated performance can not be guaranteed when it exceeds the range of the predicted value. In this paper, we propose a method to update the predicted value by using the radome slope as the mode parameter of the IMM algorithm, and confirm the radome slope estimation performance of the proposed method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.3
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• pp.228-235
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• 2010

This paper deals with an autonomous flight controller design problem for a tilt-rotor aircraft in rotary-wing mode. The inner-loop algorithm is designed using the output-based approximate feedback linearization. The model error originated from the feedback linearization is cancelled within allowable tolerance by using single-hidden-layer neural network. According to Lyapunov direct stability theory, the adaptive update law is derived to run the neural network on-line, which is based on the linear observer dynamics. Moreover, the outer-loop algorithm is designed to track the trajectory generated from way-point guidance. Especially, heading and flight-path angle line-of-sight guidance are applied to the outer-loop to improve accuracy of the landing tracking performance. The 6-DOF nonlinear simulation shows that the overall performance of the flight control algorithm is satisfactory even though the collective input response shows instantaneous actuator saturation for a short time due to the lack of the neural network and the saturation protection logic in that loop.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.453-459
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• 2008

The neural network is currently being used throughout numerous control system fields. However, it is not easy to obtain an input-output pattern when the neural network is used for the system of a single feedback controller and it is difficult to obtain satisfactory performance with when the load changes rapidly or disturbance is applied. To resolve these problems, this paper proposes a new mode to implement a neural network controller by installing a real object for control and an algorithm for this, which can replace the existing method of implementing a neural network controller by utilizing activation function at the output node. The real plant object for controlling of this mode implements a simple neural network controller replacing the activation function and provides the error back propagation path to calculate the error at the output node. As the controller is designed using a simple structure neural network, the input-output pattern problem is solved naturally and real-time learning becomes possible through the general error back propagation algorithm. The new algorithm applied neural network controller gives excellent performance for initial and tracking response and shows a robust performance for rapid load change and disturbance, in which the permissible error surpasses the range border. The effect of the proposed control algorithm was verified in a test that controlled the speed of a motor equipped with a high speed computing capable DSP on which the proposed algorithm was loaded.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.6
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• pp.37-44
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• 1999

In this paper, we present a new sliding surface with a time-varying repeated root for fast and robust tracking of higher-order uncertain systems. The repeated root is moved to target one with stabilizing the closed-loop time-varying system in sliding mode. This initial root is obtained so that shifting distance of the surface may be minimized with respect to an initial error, and the intercept is produced so that the surface may pass the initial error. Under the allowable input, fast shifting of the surface and movement of the repeated root enable the error convergence rate to be increased. The proposed sliding mode control makes the error always remain on the surface from the beginning, and therefore, the system is more insensitive to parameter uncertainties and external disturbances. In simulation, the effectiveness of the proposed method is proved by comparison with the conventional one.