• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.4
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• pp.20-29
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• 2022

The operational modal analysis (OMA) technique, which extracts the modal parameters of a structural system using ambient vibrations, has been actively developed as a field of structural health monitoring of cable-supported bridges. In this paper, the short and long-term modal parameters of a cable-stayed bridge were evaluated using the acceleration data obtained from the two ambient vibration tests (AVTs) and three years of continuous measurements. A total of 27 vertical modes and 1 lateral mode in the range 0.1 ~ 2.5 Hz were extracted from the high-resolution AVTs which were conducted in the 6th and 19th years after its completion. Existing OMA methods such as Peak-Picking (PP), Eigensystem Realization Algorithm with Data Correlation (ERADC), Frequency Domain Decomposition (FDD) and Time Domain Decomposition (TDD) were applied for modal parameters extraction, and it was confirmed that there was no significant difference between the applied methods. From the correlation analysis between long-term natural frequencies and environmental factors, it was confirmed that temperature change is the dominant factor influencing natural frequency fluctuations. It was revealed that the decreased natural frequencies of the bridge were not due to changes in structural performance and integrity, but to the environmental effects caused by the temperature difference between the two AVTs. In addition, when the TDD technique is applied, the accuracy of extracted mode shapes is improved by adding a proposed algorithm that normalizes the sequence so that the autocorrelations at zero lag equal 1.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.8
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• pp.15-26
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• 2011

In this paper, we present a new beamforming scheme for a downlink of multiuser multiple-input multipleoutput (MIMO) communication systems. Recently, a block-diagonalization (BD) algorithm has been proposed for the multiuser MIMO downlink where both a base station and each user have multiple antennas. However, the BD algorithm is not efficient when the number of supported streams per user is smaller than that of receive antennas. Since the BD method utilizes the space based on the channel matrix without considering the receive combining, the degree of freedom for beamforming cannot be fully exploited at the transmitter. In this paper, we optimize the receive beamforming vector under a zero forcing (ZF) constraint, where all inter-user interference is driven to zero. We propose an efficient algorithm to find the optimum receive vector by an iterative procedure. The proposed algorithm requires two phase values feedforward information for the receive combining vector. Also, we present another algorithm which needs only one phase value by using a decomposition of the complex general unitary matrix. Simulation results show that the proposed beamforming scheme outperforms the conventional BD algorithm in terms of error probability and obtains the diversity enhancement by utilizing the degree of freedom at the base station.

• Fire Science and Engineering
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• v.24 no.2
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• pp.106-113
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• 2010

Fire characteristics can be analyzed more realistically by using more accurate material properties related to the fire dynamics and one way to acquire these fire properties is to use one of the inverse property analyses. In this study the genetic algorithm which is frequently applied for the inverse heat transfer problems is selected to demonstrate the procedure of obtaining fire properties of the solid charring material with relatively simple chemical structure. The thermal decomposition on the surface of the test plate is occurred by receiving the radiative energy from external heat sources, and in this process the heat transfer through the test plate can be simplified by an unsteady 1-D problem. The inverse property analysis based on the genetic algorithm is then applied for the estimation of the properties related to the reaction pyrolysis. The input parameters for the analysis are the surface temperature and mass loss rate of the char plate which are determined from the unsteady 1-D analysis with a givenset of 8 properties. The estimated properties using the inverse analysis based on the genetic algorithm show acceptable agreements with the input properties used to obtain the surface temperature and mass loss rate with errors between 1.8% for the specific heat of the virgin material and 151% for the specific heat of the charred material.

• The Transactions of the Korea Information Processing Society
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• v.4 no.1
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• pp.137-148
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• 1997

Diagnostic problem solving is a major application area of knowledge-based systems research. However, most of the current approaches, both heuristic and model-based, are designed to identify single faults, and do not generalize easily to multiple fault diagnosis without exhibiting exponential behavior in the amount of computation required. In this paper, we employ a decomposition approach based on system configuration to generate an efficient algorithm for multiple fault diagnosis. The basic idea of the algorithm is to reduce the inherent combinatorial explosion that occurs in generating multiple faults by partitioning the circuit into groups that correspond to output measurement points. Rules are multiple faults by partitioning the circuit into groups that correspond to output measurement points. rules are developed for combining candidates from individual groups, and forming consistent sets of minimal candidates.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1257-1264
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• 2006

The carrier frequency offset causes loss of orthogonality between sub-carriers, thus leads to inter-carrier interference (ICI) in the OFDM symbol. This ICI causes severe degradation of the BER performance of the OFDM receiver. In this paper, we propose a new ICI cancellation algorithm which estimates frequency offset at the time-domain by using CP-ICA method to the received sub-carriers phase rotation. This algorithm is based on a statistical blind estimation method, which mainly utilizes the EVD, rotating phase and the $4^{th}-cumulants$. Since our scheme does not need any training and pilot symbol in estimation, we can expect enhanced bandwidth efficiency in OFDM systems. Simulation results show that the proposed frequency offset estimator is more accurate than the other estimators in $0.0<\varepsilon<1.0$.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.96-107
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• 1996

A voice personality transformation algorithm using orthogonal vector space conversion is proposed in this paper. Voice personality transformation is the process of changing one person's acoustic features (source) to those of another person (target). In this paper, personality transformation is achieved by changing the LPC cepstrum coefficients, excitation spectrum and pitch contour. An orthogonal vector space conversion technique is proposed to transform the LPC cepstrum coefficients. The LPC cepstrum transformation is implemented by principle component decomposition by applying the Karhunen-Loeve transformation and minimum mean-square error coordinate transformation(MSECT). Additionally, we propose a pitch contour modification method to transform the prosodic characteristics of any speaker. To do this, reference pitch patterns for source and target speaker are firstly built up, and speaker's one. The experimental results show the effectiveness of the proposed algorithm in both subjective and objective evaluations.

• Journal of Navigation and Port Research
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• v.33 no.6
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• pp.443-450
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• 2009

In this paper, we propose optimizing a remarshaling plan in an automated stacking yard using a cooperative coevolutionary algorithm (CCEA). Remarshaling is the preparation task of rearranging the containers in such a way that the delay are minimized at the time of loading. A plan for remarshaling can be obtained by the following steps: first determining the target slots to which the individual containers are to be moved and then determining the order of movement of those containers. Where a given problem can be decomposed into some subproblems, CCEA efficiently searches subproblems for a solution. In our CCEA, the remarshaling problem is decomposed into two subproblems: one is the subproblem of determining the target slots and the other is that of determining the movement priority. Simulation experiments show that our CCEA derives a plan which is better in the efficiency of both loading and remarshaling compared to other methods which are not based on the idea of problem decomposition.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.106-112
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• 2007

This paper proposes a hybrid architecture algorithm for fast computation of DCT and DFT via recursive factorization. Recursive factorization of DCT-II and DFT transform matrix leads to a similar architectural structure so that common architectural base may be used by simply adding a switching device. Linking between two transforms was derived based on matrix recursion formula. Hybrid acrchitectural design for DCT and DFT matrix decomposition were derived using the generation matrix and the trigonometric identities and relations. Data flow diagram for high-speed architecture of Cooley-Tukey type was drawn to accommodate DCT/DFT hybrid architecture. From this data flow diagram computational complexity is comparable to that of the fast DCT algorithms for moderate size of N. Further investigation is needed for multi-mode operation use of FFT architecture in other orthogonal transform computation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.3
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• pp.17-30
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• 2000

In this paper, we propose an efficient algorithm to produce 3-D surface model from a set of range data, based on NURBS (Non-Uniform Rational B-Splines) surface fitting technique. It is assumed that the range data is initially unorganized and scattered 3-D points, while their connectivity is also unknown. The proposed algorithm consists of three steps: initial model approximation, hierarchical representation, and construction of the NURBS patch network. The mitral model is approximated by polyhedral and triangular model using K-means clustering technique Then, the initial model is represented by hierarchically decomposed tree structure. Based on this, $G^1$ continuous NURBS patch network is constructed efficiently. The computational complexity as well as the modeling error is much reduced by means of hierarchical decomposition and precise approximation of the NURBS control mesh Experimental results show that the initial model as well as the NURBS patch network are constructed automatically, while the modeling error is observed to be negligible.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.4
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• pp.424-434
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• 2015

Adaptive beamforming algorithms have been widely used to remove interference and jamming in the phased array radar system. Advances in the field programmable gate array(FPGA) technology now make possible the real time processing of adaptive beamforming (ABF) algorithm. In this paper, the FPGA based real-time implementation method of adaptive beamforming system(beamformer) in the pre-processor module for active electronically scanned array(AESA) radar is proposed. A compact FPGA-based adaptive beamformer is developed using commercial off the shelf(COTS) FPGA board with communication via OpenVPX(Virtual Path Cross-connect) backplane. This beamformer comprises a number of high speed complex processing including QR decomposition & back substitution for matrix inversion and complex vector/matrix calculations. The implemented result shows that the adaptive beamforming patterns through FPGA correspond with results of simulation through Matlab. And also confirms the possibility of application in AESA radar due to the real time processing of ABF algorithm through FPGA.