• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1854-1863
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• 2003

In the recent digital communication systems, the performance of Turbo Code using the mr correction coding depends on the interleaver influencing the free distance determination and the recursive decoding algorithms that is executed in the huh decoder. However, performance depends on the interleaver depth that needs many delays over the reception process. Moreover, turbo code has been blown as the robust coding methods with the confidence over the fading channel. International Telecommunication Union(ITU) has recently adopted it as the standardization of the channel coding over the third generation mobile communications(IMT­2000). Therefore, in this paper, we preposed the interleaver that has the better performance than existing block interleaver, and modified turbo decoder that has the parallel concatenated structure using MAP algorithm. In the real­time voice and video service over third generation mobile communications, the performance of the proposed two methods was analyzed and compared with the existing methods by computer simulation in terms of reduced decoding delay using the variable decoding method over AWGN and fading channels for CDMA environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.366-369
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• 2005

Background subtraction is mainly used for the real-time extraction and tracking of moving objects from image sequences. In the outdoor environment, there are many changeable factor such as gradually changing illumination, swaying trees and suddenly moving objects, which are to be considered for the adaptive processing. Normally, GMM(Gaussian Mixture Model) is used to subtract the background adaptively considering the various changes in the scenes, and the adaptive GMMs improving the real-time performance were worked. This paper, for on-line background subtraction, applied the improved adaptive GMM, which uses the small constant for learning rate ${\alpha}$ and is not able to speedily adapt the suddenly movement of objects, So, this paper proposed and evaluated the dynamic control method of ${\alpha}$ using the adaptive selection of the number of component distributions and the global variances of pixel values.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.9
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• pp.1786-1792
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• 2007

In this paper, we proposed a recognition system for resident registration cards using ART-1 and PCA algorithm. To extract registration numbers and issue date, Sobel mask and median filter are applied first and noise removal follows. From the noise-removed image, horizontal smearing is used to extract the regions, which are binarized with recursive binarization algorithm. After that vortical smearing is applied to restore corrupted lesions, which are mainly due to the horizontal smearing. from the restored image, areas of individual codes are extracted using 4-directional edge following algorithm and face area is extracted by the morphologic characteristics of a registration card. Extracted codes are recognized using ART-1 algorithm and PCA algorithm is used to verify the face. When the proposed method was applied to 25 real registration card images, 323 characters from 325 registration numbers and 166 characters from 167 issue date numbers, were correctly recognized. The verification test with 25 forged images showed that the proposed verification algorithm is robust to detect forgery.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1067-1087
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• 2018

In a study for LiDAR data based building boundary extraction, usually dense point cloud was used to cluster building rooftop area and extract building outline. However, when we used DSM generated from stereo image matching to extract building boundary, it is not trivial to cluster building roof top area automatically due to outliers and large holes of point cloud. Thus, we propose a technique to extract building boundary semi-automatically from the DSM created from stereo images. The technique consists of watershed segmentation for using user input as markers and recursive MBR algorithm. Since the proposed method only inputs simple marker information that represents building areas within the DSM, it can create building boundary efficiently by minimizing user input.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.815-829
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• 2021

The purpose of this study is to construct a flatfish outlook model that is consistent with the "Fisheries outlook" monthly publication of the fisheries outlook center of the Korea Maritime Institute (KMI). In particular, it was designed as a partial equilibrium model limited to flatfish items, but a model was constructed with a dynamic ecological equation model (DEEM) system, considering biological breeding and shipping times. Due to limited amounts of monthly data, the market equilibrium price was calculated using a recursive model method as the inverse demand. The main research results and implications are as follows. As a result of estimating young fish inventory levels, the coefficient of the young fish inventory in the previous period was estimated to be 0.03, which was not statistically significant. Because there is distinct seasonality, when estimating the breeding outcomes, the elasticity of breeding in the previous period was found to exceed 0.7, and it increased more as the weight of the fish increased, in addition, the shipment coefficient gradually increased as the weight increased, which means that as the fish weight increased, the shipment compared to the breeding volume increased. When estimating shipments, the elasticity of breeding in previous period was estimated to respond elastically as the weight increases. The price flexibility coefficient of the total supply was inelastically estimated to be -0.19. Finally, according to a model predictive power test, the Theil U1 was estimated to be very low for all of the predictors, indicating excellent predictive power.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.281-286
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• 2023

This study analyzed the causal relationship between housing sales prices and jeonse prices in Seoul, specifically in the Gangnam and Gangbuk neighborhoods. The time-invariant Granger causality test showed bidirectional causality between the sales price and the jeonse price in Seoul and Gangbuk, but no bidirectional causality was found in Gangnam. However, the time-varying Granger causality test showed a Granger causal relationship between the housing jeonse price and the sales price for the entire period after 1993 in all three areas. Notably, the causal effect of jeonse prices on sales prices has been continuous in Gangnam since 2010. These analysis results suggest that an increase in liquidity supply to the jeonse market could increase volatility throughout the housing market, given the strong influence between the sales and jeonse markets in both directions.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.522-527
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• 2022

Object tracking is a field of signal processing that sequentially tracks the location of an object based on the previous-time location estimations and the present-time observation data. In this paper, we propose an adaptive scaling neural network that can track and adjust the scale of the input data with three recursive neural network (RNN) submodules. To evaluate object tracking performance, we compare the proposed system with the Kalman filter and the maximum likelihood object tracking scheme under an one-dimensional object movement model in which the object moves with piecewise constant acceleration. We show that the proposed scheme is generally better, in terms of root mean square error (RMSE) performance, than maximum likelihood scheme and Kalman filter and that the performance gaps grow with increased observation noise.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.375-382
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• 2016

In this paper, we presents a signatures verification by using the nonlinear quantization histogram of polar coordinate based on multi-dimensional adjacent pixel intensity difference. The multi-dimensional adjacent pixel intensity difference is calculated from an intensity difference between a pair of pixels in a horizontal, vertical, diagonal, and opposite diagonal directions centering around the reference pixel. The polar coordinate is converted from the rectangular coordinate by making a pair of horizontal and vertical difference, and diagonal and opposite diagonal difference, respectively. The nonlinear quantization histogram is also calculated from nonuniformly quantizing the polar coordinate value by using the Lloyd algorithm, which is the recursive method. The polar coordinate histogram of 4-directional intensity difference is applied not only for more considering the corelation between pixels but also for reducing the calculation load by decreasing the number of histogram. The nonlinear quantization is also applied not only to still more reflect an attribute of intensity variations between pixels but also to obtain the low level histogram. The proposed method has been applied to verified 90(3 persons * 30 signatures/person) images of 256*256 pixels based on a matching measures of city-block, Euclidean, ordinal value, and normalized cross-correlation coefficient. The experimental results show that the proposed method has a superior to the linear quantization histogram, and Euclidean distance is also the optimal matching measure.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.1
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• pp.98-106
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• 2001

This paper presents external load disturbance compensation that used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator. As a result, the response of PMSM follows that of the nominal plant. The load torque compensation method is compose of a dead beat observer that is well-known method. However it has disadvantage such as a noise amplification effect. To reduce of the effect, the post-filter, which is implemented by MA process, is proposed. The parameter compensator with RLSM(recursive least square method) parameter estimator is suggested to increase the performance of the load torque observer and main controller. Although RLSM estimator is one of the most effective methods for online parameter identification, it is difficult to obtain unbiased result in this application. It is caused by disturbed dynamic model with external torque. The proposed RLSM estimator is combined with a high performance torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation and experiment, are shown in this paper.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.155-162
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• 2008

Biological sequences such as DNA sequences and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of hundreds of frequent items. In biological sequences analysis(BSA), a frequent contiguous sequence search is one of the most important operations. Many studies have been done for mining sequential patterns efficiently. Most of the existing methods for mining sequential patterns are based on the Apriori algorithm. In particular, the prefixSpan algorithm is one of the most efficient sequential pattern mining schemes based on the Apriori algorithm. However, since the algorithm expands the sequential patterns from frequent patterns with length-1, it is not suitable for biological dataset with long frequent contiguous sequences. In recent years, the MacosVSpan algorithm was proposed based on the idea of the prefixSpan algorithm to significantly reduce its recursive process. However, the algorithm is still inefficient for mining frequent contiguous sequences from long biological data sequences. In this paper, we propose an efficient method to mine maximal frequent contiguous sequences in large biological data sequences by constructing the spanning tree with the fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. As the result, the experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.