• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1133-1138
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• 2010

In the anti-collision scheme proposed by EPCglobal Class-1 Gen-2 standard, the frame size for a query round is determined by Q-algorithm. In the Q-algorithm, the reader calculates a frame size without estimating the number of tags in it's identification range. It uses only the slot status. Therefore, Q-algorithm has advantage that the reader's algorithm is simpler than other algorithms. However, it cannot allocate an optimized frame size because it does not consider the number of tags. Also, the conventional Q-algorithm does not define an optimized parameter value C for adjusting the frame size. In this paper, we propose a modified Q-algorithm and evaluate the performance with computer simulations. The proposed Q-algorithm estimates the number of tags at every query round, and determines the parameter value C based on the estimated number of tags.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.477-483
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• 2004

This paper describes preliminary results we have obtained in developing a computer vision system based on active IR illumination for real time gaze tracking for interactive graphic display. Unlike most of the existing gaze tracking techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person our gaze tracker can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using the Generalized Regression Neural Networks(GRNN). With GRNN, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Futhermore, the mapping function can generalize to other individuals not used in the training. The effectiveness of our gaze tracker is demonstrated by preliminary experiments that involve gaze-contingent interactive graphic display.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1531-1538
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• 2015

In this paper, we proposed receiver structure based on an iterative turbo equalization to cope with phase difference between two sensors in MIMO underwater communication channel. In a space-time coded system, it is often assumed that there are no phase errors among the multiple transmitter and receiver chains. In this paper, we have studied the effect of the phase errors between different transmit sensors and different propagation paths in the environment of MIMO underwater communication system, and have shown through BER performance by computer simulations that the bit-error-rate performance can be severely degraded. A decision-directed estimation and compensation algorithm has been proposed to minimize their effects on the system performance. In this paper, we investigate the phase differences and their effects on multiple-input and multiple-output systems, and propose a compensation algorithm for underwater channel model to minimize their effects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1327-1333
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• 2018

Numerical analysis has the advantage that no actual flow pathways need to be formulated, making this technique especially useful for simulation analysis such as pathway design. However, it does require that the complete physical parameters of the fluid and the complete boundary conditions be known. If any of them are unknown, either the calculation will become impossible, or even if the calculation does converge, the reliability of the result will be low. Therefore, a means of more accurate acquisition of flow information is required. In this paper, we present techniques for estimating flow field from a constraint equation for image information and velocity field, based on the image intensity changes accompanying the motion of dye in waterway. In the equation, we entered a stabilizing term to suppress estimation error. We show the effectiveness of our method through experiments with generated and real images of a Karman vortex.

• Journal of Korea Water Resources Association
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• v.41 no.10
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• pp.1059-1065
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• 2008

Rainfall data is the most basic input data to analyze the hydrological phenomena and can be missing due to various reasons. In this research, a neural network based model to estimate missing rainfall data as approximate values was developed for 12 rainfall stations in the Soyang river basin to improve existing methods. This approach using neural network has shown to be useful in many applications to deal with complicated natural phenomena and displayed better results compared to the popular offline estimating methods, such as RDS(Reciprocal Distance Squared) method and AMM(Arithmetic Mean Method). Additionally, we proposed automated data reconciliation systems composed of a neural network learning processer to be capable of real-time reconciliation to transmit reliable hydrological data online.

• Journal of Korean Society on Water Environment
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• v.27 no.6
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• pp.896-904
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• 2011

The features of the capture reaction of $CO_2$ by ammonia solution have been investigated along with the effect of temperature on the reaction based upon computer program-utilizing calculation and thermodynamic estimation. The stable region of $CO{_3}^{2-}$ was observed to increase with temperature and the change of the stable region of $CO{_3}^{2-}$ with temperature was greater than the temperature variation of the stable region of other carbonate species. The distribution diagram for $NH_4{^+}-NH_3$ system was constructed and the rise of temperature resulted in the decrease of the stability of $NH_4{^+}$ ion, which was thought to be due to the endothermic nature of its acidic dissociation. Considering the introduction of $Ca^{2+}$ ion in the carbon capture reaction by $NH_4{^+}$, the temperature was observed to be important in the determination of the order of reaction between carbonate ion and these cations. The removal process of $CO_2$ gas by ammonia solution was presumed to occur in open system and the temperature variations of the concentration of carbonate system species along with their total concentration were calculated for the proper control and design of the real process.

• Journal of IKEEE
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• v.24 no.4
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• pp.1081-1085
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• 2020

Instantaneous frequencies (IF) of the AM-FM signal is estimated based on the inflection point detection (IPD) method. Local maxima/minima are detected using the IPD, and they are exploited to find the IF of AM and FM components, respectively. The envelope of the maxima/minima is obtained to estimate the IF of the AM part. And the distance between neighboring maxima (or minima) is used to estimate the IF of the FM component. Computer simulation shows that the proposed method properly estimates the IF of the AM and FM when the signal has fixed frequencies for both parts. In the case of the time-varying IF of the FM part, the estimated IF shows some deviation from the true IF due to the rough sampling effect of the maximum/minimum points. Thus, the post-processing such as the lowpass filtering of the estimated IF is required to refine the resulting IF estimation.

• Journal of IKEEE
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• v.27 no.4
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• pp.472-476
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• 2023

Fundamental frequency/pitch period are major characteristics of speech signals. They are used in many speech applications like speech coding, speech recognition, speaker identification, and so on. In this paper, some of inflection points are used to estimate the pitch which is the inverse of the fundamental frequency. The inflection points are defined as points where local maxima, local minima or the slope changes occur. The speech signal is preprocessed to remove unnecessary inflection points due to the high frequency components using a low pass filter. Only the inflection points from local maxima are used to get the pitch period. While the existing pitch estimation methods process speech signals in blockwise, the proposed method detects the inflection points in sample and produces the pitch period/fundamental frequency estimates along the time. Computer simulation shows the usefulness of the proposed method as a fundamental frequency estimator.

• Journal of Broadcast Engineering
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• v.14 no.3
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• pp.322-331
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• 2009

This paper proposes an efficient data representation of stereo images using edge-based mesh optimization. Mash-based two dimensional warping for stereo images mainly depends on the performance of a node selection and a disparity estimation of selected nodes. Therefore, the proposed method first of all constructs the feature map which consists of both strong edges and boundary lines of objects for node selection and then generates a grid-based mesh structure using initial nodes. The displacement of each nodal position is iteratively estimated by minimizing the predicted errors between target image and predicted image after two dimensional warping for local area. Generally, iterative two dimensional warping for optimized nodal position required a high time complexity. To overcome this problem, we assume that input stereo images are only horizontal disparity and that optimal nodal position is located on the edge include object boundary lines. Therefore, proposed iterative warping method performs searching process to find optimal nodal position only on edge lines along the horizontal lines. In the experiments, we compare our proposed method with the other mesh-based methods with respect to the quality by using Peak Signal to Noise Ratio (PSNR) according to the number of nodes. Furthermore, computational complexity for an optimal mesh generation is also estimated. Therefore, we have the results that our proposed method provides an efficient stereo image representation not only fast optimal mesh generation but also decreasing of quality deterioration in spite of a small number of nodes through our experiments.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.689-700
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• 2017

This paper presents an effective approach for wind turbine (WT) condition assessment based on the data collected from wind farm supervisory control and data acquisition (SCADA) system. Three types of assessment indices are determined based on the monitoring parameters obtained from the SCADA system. Neural Networks (NNs) are used to establish prediction models for the assessment indices that are dependent on environmental conditions such as ambient temperature and wind speed. An abnormal level index (ALI) is defined to quantify the abnormal level of the proposed indices. Prediction errors of the prediction models follow a normal distribution. Thus, the ALIs can be calculated based on the probability density function of normal distribution. For other assessment indices, the ALIs are calculated by the nonparametric estimation based cumulative probability density function. A Back-Propagation NN (BPNN) algorithm is used for the overall WT condition assessment. The inputs to the BPNN are the ALIs of the proposed indices. The network structure and the number of nodes in the hidden layer are carefully chosen when the BPNN model is being trained. The condition assessment method has been used for real 1.5 MW WTs with doubly fed induction generators. Results show that the proposed assessment method could effectively predict the change of operating conditions prior to fault occurrences and provide early alarming of the developing faults of WTs.