• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.74-79
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• 2008

CR technology is an intelligent technology which can sense the spectrum environment an adaptively adjust the parameters for wireless transmission. In this paper, by using CR-UWB, the spectrum efficiency of the transmission channel is largely improved; Furthermore, the interference to other system can be effectively avoided. In this paper, we propose a solution on interference problem of UWB system using cognitive radio. We use interference temperature model of cognitive radio that has proposed by FCC for estimating interference signal. Calculating channel capacity of UWB system with interference temperature, we suggest how to solve interference problem. We have used genetic algorithm in cognitive engine's calculation precess. The proposed UWB System with cognitive radio shows very efficient in solving interference problem.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3660-3665
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• 2012

For blind equalization, it is necessary to open an eye pattern quickly in the early stage of equalization, after that it is important to lower an error level of equalizer output signal. This paper discusses coarse error estimation using signal points specifically determined and fine error estimation using original signal constellation, and proposes two suggestions for how to take advantage of the two error estimation methods. The two error estimates, respectively, are effective to quickly open an eye pattern in the state of eye pattern closed, or to lower the level of an error in the steady-state after the eye pattern opening. Two blind equalization algorithms are proposed and their performances are compared, which select one of the two error estimates depending on the state of convergence of the equalizer, or combine two errors weightedly according to the relative reliabilities of the two error estimates, and calculate the new error.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.431-437
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• 2017

In this study, based on the RPS algorithm, the application results to an electrically controlled suspension system using previewed road information are presented. Reducing the excessive vibration induced by a disturbance transmitted to the system and secure its stability is a major issue. In particular, in the automotive industry, the demand is constantly being raised. A typical external disturbance causing vibration and instability of a vehicle is an irregular roadway surface that contacts a running vehicle tire. Therefore, obtaining such profile information is an important process. The RPS algorithm using a multi sensor system was constructed and implemented in a real car. Through experimental work using the RPS system included non-contact type optical sensors, it could robustly reconstruct the road input profiles from the intermixed data onto the vehicle's dynamic motion while traveling at an uneven roadway surface. A controller with a preview control was designed in the framework of a semi-active suspension system based on the 7 degrees of freedom full vehicle model. The control performance of the system was evaluated through simulations and the results were compared with the passive vehicle condition. These results highlight the feasibility of the presented control frame.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.395-400
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• 2011

In this paper, we propose an study of the facial emotion recognition considering the dynamical variation of emotional state in facial image sequences. The proposed system consists of two main step: facial image based emotional feature extraction and emotional state classification/recognition. At first, we propose a method for extracting and analyzing the emotional feature region using a combination of Active Shape Model (ASM) and Facial Action Units (FAUs). And then, it is proposed that emotional state classification and recognition method based on Hidden Markov Model (HMM) type of dynamic Bayesian network. Also, we adopt a Harmony Search (HS) algorithm based heuristic optimization procedure in a parameter learning of HMM in order to classify the emotional state more accurately. By using all these methods, we construct the emotion recognition system based on variations of the dynamic facial image sequence and make an attempt at improvement of the recognition performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.8
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• pp.1424-1433
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• 2007

In this paper, we propose a hardware architecture to generate digital hologram using the modified CGH (Computer Generated Hologram) algorithm for hardware implementation and design to FPGA (Field Programmable Gate Array) platform. After analyzing the CGH algorithm, we propose an architecture of CGH cell which efficiently products digital hologram, and design CGH Kernel from configuring CGH Cell. Finally we implement CGH Processor using CGH Kernel, SDRAM Controller, DMA, etc. Performance of the proposed hardware can be proportionally increased through simply addition of CGH Cell in CGH Kernel, since a CGH Cell has operational independency. The proposed hardware was implemented using XC2VP70 FPGA of Xilinx and was stably operated in 200MHz clock frequency. It take 0.205 second for generating $1,280{\times}1,024$ digital hologram from 3 dimensional object which has 40,000 light sources.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.1009-1018
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• 2019

This paper describes the design and implementation of a rehabilitation medical device based on a EMG measurement. Rehabilitation systems are controlled using BLDC motors and motor drives. The BLDC motor drive controls the operation and the speed controls the drive through the external servo motor. In addition, potentiometer coupled to the outside of the motor transmits information about the position of the load being rotated by the motor. The rehabilitation algorithm is controlled by limiting the maximum angle of 0 to 120 by utilizing the motor according to the user setting stage during the rehabilitation exercise. The walking algorithm compensates motor control for the low leg of the signal using the difference value of the signal obtained with the surface denser attached to both inner muscles. The motor and surface denser are utilized for the walk motion to control the maximum angle of 0 to 80.

• Journal of the Korea Society for Simulation
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• v.29 no.3
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• pp.9-18
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• 2020

The development of a large-scale thermal power plant control simulator consists of water/steam systems, air/combustion systems, pulverizer systems and turbine/generator systems. Modeling is possible for all systems except mechanical turbines/generators. Currently, there have been attempts to develop neural network simulators for some systems of a boiler, but the development of simulator for the whole system has never been completed. In particular, autoTuning, one of the key technology developments of all power generation companies, is a technology that can be achieved only when modeling for all systems with high accuracy is completed. The simulation results show accuracy of 95 to 99% or more of the actual boiler system, so if the field PID controller is fitted to this simulator, it will be available for fault diagnosis or auto-tuning.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.113-121
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• 2020

With the rapid development of information and communication technology (ICT), various sensors are being embedded in wearable devices. Consequently, these devices can continuously collect data including health data from individuals. The collected health data can be used not only for healthcare services but also for analyzing an individual's lifestyle by combining with other external data. This helps in making an individual's life more convenient and healthier. However, collecting health data may lead to privacy issues since the data is personal, and can reveal sensitive insights about the individual. Thus, in this paper, we present a method to collect an individual's health data from a smart band in a privacy-preserving manner. We leverage the local differential privacy to achieve our goal. Additionally, we propose a way to find feature points from health data. This allows for an effective trade-off between the degree of privacy and accuracy. We carry out experiments to demonstrate the effectiveness of our proposed approach and the results show that, with the proposed method, the error rate can be reduced upto 77%.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.291-297
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• 2018

Due to difficulty in minimally invasive surgery, training simulator is actively researched. A volumetric deformable organ is created by employing a shape-retaining chain-linked (S-chain) model to realize positioning a human organ model in virtual space. Since the main principle of the S-chain algorithm is that the repulsive force is proportional to the number of chain elements, the calculation time can be increased according to the magnitude of deformation. In this work, the advanced S-chain algorithm is used to calculate the repulsive torque according to spin motion. Finally, haptic architecture was constructed using this S-chain model by incorporating the virtual organ with a real master device, which allows the repulsive force and target position to be transferred to each other. The control performance of S-chain algorithm has been evaluated via experiment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.127-132
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• 2019

Influenza is an infectious disease caused by an influenza virus with symptoms of high fever and headache. Since influenza especially mutates into multiple subtypes in the carrier's body, it is a serious threat for mankind such as Spanish influenza. The treatment of influenza infection mandates the use of antiviral drugs through rapid diagnostic test. Generally, immunochromatography-based rapid influenza diagnostic tests are used for rapid diagnosis in an emergency. In this paper, we propose an influenza analysis algorithm based on image processing to examine a large number of patients suspected of being infected with influenza. Also, we propose a robust influenza analysis algorithm based on the joint cumulative mass function under varying radiometric conditions such as illuminant and exposure differences. Simulation results show that the proposed algorithm significantly reduces the error of influenza diagnosis under different radiometric conditions.