• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.51-64
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• 2004

This paper proposes an algerian of generating a tuner-template from multiple fingerprint impressions using a data fusion technique for fingerprint enrollment. The super-template is considered as a single fingerprint template which contains most likely true minutiae based on multiple fingerprint images. The proposed algorithm creates the super template by utilizing a recursive Bayesian estimation method (RBEM), which assumes a sequential fingerprint input model and estimates the credibility of the minutiae in previous input templates froma current input template. Consequently. the RBEM assigns a higher credibility to commonly detectable minutiae from several input templates and a lower credibility to rarely found minutiae from other input templates. Likewise, the RBEM is able to estimate a credibility of the minutia type (ridge ending or bifurcation). Preliminary experiments demonstrate that, as the number of fingerfrint images increases, the performance of recognition can be improved while maintaining the processing time and the size of memory storage for tile super-template almost constant.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.47-53
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• 2007

True motion estimation is necessary for deinterlacing, frame-rate conversion, and film judder compensation. There have been several block-based approaches to find true motion vectors by tracing minimum sum-of-absolute-difference (SAD) values by considering spatial and temporal consistency. However, the algorithms cannot find robust motion vectors when the texture of objects is changed. To find the robust motion vectors in the region, a recursive vector selection scheme and an adaptive weighting parameter are proposed. Previous frame vectors are recursively averaged to be utilized for motion error region. The weighting parameter controls fidelity to input vectors and the recursively averaged ones, where the input vectors come from the conventional estimators. If the input vectors are not reliable, then the mean vectors of the previous frame are used for temporal consistency. Experimental results show more robust motion vectors than those of the conventional methods in time-varying texture objects.

• Journal of the Korea Concrete Institute
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• v.17 no.6 s.90
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• pp.939-946
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• 2005

The stiffness properties of heterogeneous concrete materials and their degradation were investigated at different-levels of observations with aids of the opportunities and limitations of multi-resolution wavelet analysis. The successive Haw transformations lead to a recursive separation of the stiffness properties and the response into coarse-and fine-scale features. In the limit, this recursive process results in a homogenization parameter which is an average measure of stiffness and strain energy capacity at the coarse scale. The basic concept of multi-resolution analysis is illustrated with one and two-dimensional model problems of a two-phase particulate composite representative of the morphology of concrete materials. The computational studies include the meso-structural features of concrete in the form of a hi-material system of aggregate particles which are immersed in a hardened cement paste taking due to account of the mismatch of the two elastic constituents.

• Journal of Navigation and Port Research
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• v.33 no.5
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• pp.323-330
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• 2009

We have been developing an underwater robot for harbour construction using a parallel mechanism The robot is attached to the rope of a crane, which curries a large stone into the undersea The robot's yaw and pitch are controlled by hydraulic cylinders but its roll is uncontrollable. We mount propellers in both side of the robot to generate the roll motion This paper studies on the control for the roll motion of a underwater robot. A gyro-sensor is used to measure the angle in a roll motion We develop the dynamic model to describe the robot's roll motion by a second order non-linear system and identify the model parameters by recursive least square and adaptive identifier. PD control, recursive model based control and adaptive model based control are applied with the dynamic model which computes the control input to compensate disturbances. This paper introduces the underwater robot system and presents the simulated and experimental results of the proposed controller.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.3
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• pp.239-246
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• 2014

In the context of wireless sensor networks, one of major issues is energy conservation. For low power communication, by utilizing our experimental results for the relation between clock drift and synchronization interval, we designed a new protocol which can support a wide range of duty cycles for applications with very low traffic rate and insensitive delay. The transmission (TX) node in the protocol synchronizes with the reception (RX) node very before transmitting a packet, and it can adaptively estimate the synchronization error size according to the synchronization interval from minutes to hours. We conducted simulations and a testbed implementation to show the efficacy of the proposed protocol. We found that our protocol substantially outperforms other state-of-the-art protocols, resulting in order-of-magnitude increase in network lifetime over a variety of duty cycles.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.67-79
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• 2011

The statistical process control (SPC) assumes that observations follow the particular statistical distribution and they are independent to each other. However, the time-series data do not always follow the particular distribution, and most of cases are autocorrelated, therefore, it has limit to adopt the general SPC in tim series process. In this study, we propose a MPBC (Model Parameter Based Control-chart) method for fault detection in time-series processes. The MPBC builds up the process as a time-series model, and it can determine the faults by detecting changes parameters in the model. The process we analyze in the study assumes that the data follow the ARMA (p,q) model. The MPBC estimates model parameters using RLS (Recursive Least Square), and $K^2$-control chart is used for detecting out-of control process. The results of simulations support the idea that our proposed method performs better in time-series process.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.3
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• pp.18-25
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• 2005

Existing methods have performed the reliability analysis using nonlinear optimization techniques. This is mainly due to the fact that they directly apply Multidisciplinary Design Optimization(MDO) frameworks to the reliability analysis formulation. Accordingly, the reliability analysis and the Multidisciplinary Analysis(MDA) are tightly coupled in a single optimizer, which hampers utilizing the recursive and function-approximation based reliability analysis methods such as the Advanced First Order Reliability Method(AFORM). In order to utilize the efficient reliability analysis method under multidisciplinary analysis systems, we propose a new strategy named Sequential Approach on Reliability Analysis under Multidisciplinary analysis systems(SARAM). In this approach, the reliability analysis and the MDA are decomposed and arranged in a sequential manner, making a recursive loop. The efficiency of the SARAM method was verified using three illustrative examples taken from the literatures. Compared with existing methods, it showed the least number of subsystem analyses over other methods while maintaining accuracy.

• International Area Studies Review
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• v.14 no.3
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• pp.246-263
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• 2010

This study examines how the long-run relations between housing price and inflation in the United Sates have changed since the year of 2000. Johansen co-integration test, estimation of long-run equilibrium equation, and Granger causality tests are conducted, based on the VECM. Data covers the period from the first quarter of 1975 to the second quarter of 2010. I adopt the recursive estimation method in which the final period of the estimation is expanded by one quarter, starting from the first quarter of 2000. The empirical results are as follows: (1) In spite of the sharp increase of housing price, the long-run relationship of house prices and inflation has been remained stable until 2007, showing that house prices are a stable inflation hedge in the long run. (2) The housing price plunge since 1997 does not seem to be related to the restore of the long-run relationship between housing prices and inflation. (3) Granger causality test results support the hypothesis that inflation granger-causes housing prices with 10% significance level, but reject the hypothesis that housing price granger-causes inflation.

• International Area Studies Review
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• v.21 no.4
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• pp.159-172
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• 2017

In a typical trend-cycle decomposition of GDP, the trend component is usually assumed to follow a random walk process. This paper considers an ARIMA trend and assesses the validity of the ARIMA trend model. I construct univariate and bivariate unobserved-components(UC) models, allowing the ARIMA trend. Estimation results using U.S. data are favorable to the ARIMA trend models. I, also, compare the forecasting performance of the UC models. Dynamic pseudo-out-of-sample forecasting exercises are implemented with recursive estimations. I find that the bivariate model outperforms the univariate model, the smoothed estimates of trend and cycle components deliver smaller forecasting errors compared to the filtered estimates, and, most importantly, allowing for the ARIMA trend can lead to statistically significant gains in forecast accuracy, providing support for the ARIMA trend model. It is worthy of notice that trend shocks play the main source of the output fluctuation if the ARIMA trend is allowed in the UC model.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.4
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• pp.41-49
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• 2009

In ubiquitous sensor networks, sensor nodes can be compromised by an adversary since they are deployed in hostile environments. False sensing reports can be injected into the network through these compromised nodes, which may cause not only false alarms but also the depletion of limited energy resource in the network. In the security solutions for the filtering of false reports, the choice of a security threshold value which determines the security level is important. In the existing adaptive solutions, a newly determined threshold value is broadcasted to the whole nodes, so that extra energy resource may be consumed unnecessarily. In this paper, we propose an application of the recursive contract net protocol to determine the threshold value which can provide both energy efficiency and sufficient security level. To manage the network more efficiently, the network is hierarchically grouped, and the contract net protocol is applied to each group. Through the protocol, the threshold value determined by the base station using a fuzzy logic is applied only where the security attack occurs on.