• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.6
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• pp.726-735
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• 2003

A Process of 3-D Particle image velocimetry, called here, as '3-D volume PIV' was developed for the full-field measurement of 3-D complex flows. The present method includes the coordinate transformation from image to camera, calibration of camera by a calibrator based on the collinear equation, stereo matching of particles by the approximation of the epipolar lines, accurate calculation of 3-D particle positions, identification of velocity vectors by 3-D cross-correlation equation, removal of error vectors by a statistical method followed by a continuity equation criterior, and finally 3-D animation as the post processing. In principle, as two frame images only are necessary for the single instantaneous analysis 3-D flow field, more effective vectors are obtainable contrary to the previous multi-frame vector algorithm. An Experimental system was also used for the application of the proposed method. Three analog CCD camera and a Halogen lamp illumination were adopted to capture the wake flow behind a bluff obstacle. Among 200 effective particle s in two consecutive frames, 170 vectors were obtained averagely in the present study.

• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.753-768
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• 2003

In this paper, we propose a multi-dimensional index structure, tailed a VA(Vector Approximate)-tree that is constructed with vector approximates of multi-dimensional feature vectors. To save storage space for index structures, the VA-tree employs vector approximation concepts of VA-file that presents feature vectors with much smaller number of bits than original value. Since the VA-tree is a tree structure, it does not suffer from performance degradation owing to the increase of data. Also, even though the VA-tree is MBR(Minimum Bounding Region) based tree structure like a R-tree, its split algorithm never allows overlap between MBRs. We show through various experiments that our proposed VA-tree is a suitable index structure for large amount of multi-dimensional data.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.5
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• pp.680-687
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• 2014

PGA(phase gradient autofocus) has been widely used to remove motion induced phase errors in the ISAR(inverse synthetic aperture radar) imaging. The critical process for the processing time and image quality is windowing stage in PGA. In this paper, the new method to determine window size based on polynomial least square approximation is proposed. Moreover, dominant range bins are selected for efficient phase error estimation, which improve image quality and speed up convergence. The simulation results show that the proposed algorithm provides high quality ISAR images while computational efficiency of inherent PGA is retained.

• Journal of Broadcast Engineering
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• v.2 no.1
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• pp.1-7
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• 1997

In this paper, a microstrip patch antenna was analyzed by using FDTD method. Firstly, the electric field in the microstrip patch antenna was obtained by approximating a Maxwell's equation to a finite difference equation by means of Yee's algorithm. In this case, Mur's 1st approximation and dispersive boundary condition(BBC) were applied to an absorbing boundary condition. We also analyzed a single microstrip patch antenna by using the FDTD method, then calculating the propagative process in the wave of a return loss. Also, as the result that FDTD was applied to 2-array antenna designed to increase the gain of antenna, the measured results was in relatively good accordance with the values calculated by the FDTD method. The calculated impedance, return loss and VSWR were comparatively good. And these results were In relatively good accordance with the measured values.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.57-66
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• 2005

In this paper, we propose a method to evaluate the solutions of the renewal equations related to SPRT for Erlang distribution. In SPRT, the Average Sample Number(ASN) and type I or type II error probabilities are shown in Fredholm type integral equations. The integral equations are generally solved by the approximation method using Gaussian quadrature. For Erlang distribution, it has been known that the exact solutions of the equations exist. We propose the algorithm to solve the equations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.253-271
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• 2017

In this paper, considering that perfect channel state information (CSI) is hard to achieve in practice, the downlink capacity of distributed antenna systems (DAS) with imperfect CSI and multiple receive antennas is investigated over composite Rayleigh fading channel. According to the performance analysis, using the numerical calculation, the probability density function (PDF) of the effective output SNR is derived. With this PDF, accurate closed-form expressions of ergodic capacity and outage probability of DAS with imperfect CSI are, respectively, obtained, and they include the ones under perfect CSI as special cases. Besides, the outage capacity of DAS in the presence of imperfect CSI is also derived, and a Newton's method based practical iterative algorithm is proposed to find the accurate outage capacity. By utilizing the Gaussian distribution approximation, another approximate closed-form expression of outage capacity is also derived, and it may simplify the calculation of accurate outage capacity. These theoretical expressions can provide good performance evaluation for downlink DAS for both perfect and imperfect CSI. Simulation results verify the effectiveness of the theoretical analysis, and the system capacity can be improved by increasing the receive antennas, and decreasing the estimation error or path loss. Moreover, the system can tolerate the estimation error variance up to about 0.01 with a slight degradation in the capacity.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.4
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• pp.326-337
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• 2010

This work addresses problems regarding trajectory planning for unmanned aerial vehicle sensors. Such sensors are used for taking measurements of large nonlinear systems. The sensor investigations presented here entails methods for improving estimations and predictions of large nonlinear systems. Thoroughly understanding the global system state typically requires probabilistic state estimation. Thus, in order to meet this requirement, the goal is to find trajectories such that the measurements along each trajectory minimize the expected error of the predicted state of the system. The considerable nonlinearity of the dynamics governing these systems necessitates the use of computationally costly Monte-Carlo estimation techniques, which are needed to update the state distribution over time. This computational burden renders planning to be infeasible since the search process must calculate the covariance of the posterior state estimate for each candidate path. To resolve this challenge, this work proposes to replace the computationally intensive numerical prediction process with an approximate covariance dynamics model learned using a nonlinear time-series regression. The use of autoregressive time-series featuring a regularized least squares algorithm facilitates the learning of accurate and efficient parametric models. The learned covariance dynamics are demonstrated to outperform other approximation strategies, such as linearization and partial ensemble propagation, when used for trajectory optimization, in terms of accuracy and speed, with examples of simplified weather forecasting.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.1
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• pp.153-158
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• 2006

To optimize the combustion system in a HSDI diesel engine, a new analysis technology was developed. The in-cylinder 3-D combustion analysis was carried out by the modified KIVA-3V, and the spray characteristics for the high pressure injection system were analyzed by HYDSIM. The combustion design parameters were optimized by coupling the KIVA-3V and the iSIGHT. The optimization procedure consists of 3 steps. The $1^{st}$ step is the sampling method by the Design of Experiment(DOE), the $2^{nd}$ step is the approximation using the Neural Network method, and the $3^{rd}$ step is the optimization using the Genetic Algorithm. The developed procedures have been approved as very effective and reliable, and the computational results agree well with the experimental data. The analysis results show that the optimized combustion system in a HSDI diesel engine is capable of reducing NOx and Soot emissions simultaneously keeping a same level of the fuel consumption(BSFC).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.4087-4102
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• 2014

Two-way relaying is an effective way of improving system spectral efficiency by making use of physical layer network coding. However, energy efficiency in OFDM-based bidirectional relaying with asymmetric traffic requirement has not been investigated. In this study, we focused on subcarrier transmission mode selection, bit loading, and power allocation in a multicarrier single amplified-and-forward relay system. In this scheme, each subcarrier can operate in two transmission modes: one-way relaying and two-way relaying. The problem is formulated as a mixed integer programming problem. We adopt a structural approximation optimization method that first decouples the original problem into two suboptimal problems with fixed subcarrier subsets and then finds the optimal subcarrier assignment subsets. Although the suboptimal problems are nonconvex, the results obtained for a single-tone system are used to transform them to convex problems. To find the optimal subcarrier assignment subsets, an iterative algorithm based on subcarrier ranking and matching is developed. Simulation results show that the proposed method can improve system performance compared with conventional methods. Some interesting insights are also obtained via simulation.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.6 no.7
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• pp.37-47
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• 1995

In this paper, we have measured eletromagnetic noises from eletcric trains and the measurment data are treated statisticlly for monig. In order to measure the noise of electric tran, we set up an automatic measuring system andd measured the magnetic field over 9 kHz ~ 30 MHz range and electric field over 30 MHz - 1, 000 MHz range. The computer controlled measurint system yields efficiently experimental APD (Amplitude Probability distribution) data each of national rail road and subway train. The measured APD curves are analysed in terms of sensitivity study of Middleton's model through 6-parameter variation. Optimal parameters are obtained from measured data using Composite Approximation Algorithm.