• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7A
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• pp.689-695
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• 2006

This paper focuses on the accurate performance evaluation of cooperative diversity technique with imperfect channel estimates. The channel environment for simulations and performance evaluation is supposed to be the slowly time-varying Rayleigh fading channel. The framework of the performance evaluation is based on the Moment Generating Function(MGF) approach. To apply the effect of this channel estimation error into the performance evaluation, we import an useful Gaussian approximation in formulating the effective noise component and the additive noise. The average BER performance of cooperative diversity with M-PSK and M-QAM is computed as a function of the ratio of the signal to the effective noise based on the approximation. The verification of computed performance is provided with simulations. The evaluated performance matches up to simulation results even in a low SNR region.

• Journal of Ocean Engineering and Technology
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• v.33 no.1
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• pp.76-84
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• 2019

For decades, solitary waves have commonly been used to simulate tsunami conditions in numerical studies. However, the main component of a tsunami waveform acts at completely different spatial and temporal distributions than a solitary waveform. Thus, this study applied a 2-D numerical wave tank that included a non-reflected tsunami generation system based on Navier-Stokes equations (LES-WASS-2D) to directly simulate the run-up of a tsunami-like solitary wave on a slope. First, the waveform and velocity due to the virtual depth factor were applied to the numerical wave tank to generate a tsunami, which made it possible to generate the wide waveform of a tsunami, which was not reproduced with the existing solitary wave approximation theory. Then, to validate the applied numerical model, the validity and effectiveness of the numerical wave tank were verified by comparing the results with the results of a laboratory experiment on a tsunami run-up on a smooth impermeable 1:19.85 slope. Using the numerical results, the run-up characteristics due to a tsunami-like solitary wave on an impermeable slope were also discussed in relation to the volume ratio. The maximum run-up heights increased with the ratio of the tsunami waveform. Therefore, the tsunami run-up is highly likely to be underestimated compared to a real tsunami if the solitary wave of the approximation theory is applied in a tsunami simulation in a coastal region.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.593-601
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• 2016

This paper is related to the Region-based Spectral Correlation Estimation(RSCE) coding method that makes it possible to achieve the high-compression ratio by estimating color component images from luminance image. The proposed method is composed of three steps. First, Y/C bit-plane summation image is defined using normalized chrominance summation image and luminance image, and then the Y/C bit-plane summation image is segmented for extracting the shape information of the regions. Secondly, the scale factor and the offset factor minimizing the approximation square errors between luminance image and R, B images by the each region are calculated. Finally, the scale factor and the offset factor for the each region are encoded into bit stream. Referring to the results of computer simulation, the proposed method provides more than two or three times higher compression ratio than JPEG/Baseline or JPEG2000/EBCOT algorithm in terms of bpp needed for encoding two color component images with the same PSNR.

• Structural Engineering and Mechanics
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• v.75 no.4
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• pp.519-527
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• 2020

Dynamic analysis of a vehicle-track coupling system is important to structural design, damage detection and condition assessment of the structural system. Deterministic analysis of the vehicle-track coupling system has been extensively studied in the past, however, the structural parameters of the coupling system have uncertainties in engineering practices. It is essential to treat the parameters of the vehicle-track coupling system with consideration of uncertainties. In this paper, a method for predicting the bounds of the vehicle-track coupling system responses with uncertain parameters is presented. The uncertain system parameters are modeled as fuzzy variables instead of conventional random variables with known probability distributions. Then, the dynamic response functions of the coupling system are transformed into a component function based on the high dimensional representation approximation. The Lagrange interpolation method is used to approximate the component function. Finally, the bounds of the system's dynamic responses can be predicted by using Monte Carlo method for the interpolation polynomials of the Lagrange interpolation function. A numerical example is introduced to illustrate the ability of the proposed method to predict the bounds of the system's dynamic responses, and the results are compared with the direct Monte Carlo method. The results show that the proposed method is effective and efficient to predict the bounds of the system's dynamic responses with fuzzy variables.

• Ocean and Polar Research
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• v.26 no.3
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• pp.489-499
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• 2004

The climatological characteristics of the polar ionospheric currents obtained from the simultaneous observations of the ionospheric electric field and conductivity are examined. For this purpose, 43 and 109 days of measurements from the Chatanika and Sondrestrom incoherent scatter radars are utilized respectively. The ionospheric current density is compared with the corresponding ground magnetic disturbance. Several interesting characteristics about the polar ionosphere are apparent from this study: (1) The sun determines largely the conductance over the Sondrestrom radar, while the nighttime conductance distribution over the Chatanika radar is significantly affected by auroral precipitation. (2) The regions of the maximum N-S electric field over the Chatanika radar are located approximately at the dawn and dusk sectors, while they tend to shift towards dayside over the Sondrestrom radar. The N-S component over Son-drestrom is slightly stronger than Chatanika. However, the E-W component over Chatanika is negligible compared to that of Sondrestrom. (3) The E-W ionospheric current flows dominantly in the night hemisphere over Chatanika, while it flows in the sunlit hemisphere over Sondrestrom. The N-S current over Chatanika flows prominently in the dawn and dusk sectors, while a strong southward current flows in the prenoon sector over Sondrestrom. (4) The assumption of infinite sheet current approximation is far from realistic, underestimating the current density by a factor of 2 or more. It is particularly serious for the higher latitude region. (5) The correlation between ${\Delta}H\;and\;J_E$ is higher than the one between ${\Delta}D\;and\;J_N$, indicating that field-aligned current affects ${\Delta}D$significantly.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.117-124
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• 2014

Cluttered background is a major obstacle in developing salient object detection and tracking system for mobile device captured natural scene video frames. In this paper we propose a context aware feature vector selection model to provide an efficient noise filtering by machine learning based classifiers. Since the context awareness for feature selection is achieved by searching nearest neighborhoods, known as NP hard problem, we apply a fast approximation method with complexity analysis in details. Separability enhancement in feature vector space by adding the context aware feature subsets is studied rigorously using principal component analysis (PCA). Overall performance enhancement is quantified by the statistical measures in terms of the various machine learning models including MLP, SVM, Naïve Bayesian, CART. Summary of computational costs and performance enhancement is also presented.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.35-44
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• 2009

The emerging notion of data stream has brought many new challenges to the research communities as a consequence of its conceptual difference with conventional concepts of just data. One typical example is data stream processing in sensor networks. The range of data processing considerations in a sensor network is very wide, from physical resource restrictions such as bandwidth, energy, and memory to the peculiarities of query processing including continuous and specific types of queries. In this paper, as one of the physical constraints in data stream processing, we consider the problem of limited memory and propose a new scheme for data stream reduction based on the Principal Component Analysis (PCA) technique. PCA can transform a number of (possibly) correlated variables into a (smaller) number of uncorrelated variables. We adapt PCA for the data stream of a sensor network assuming the cooperation of a query engine (or application) with a network base station. Our method exploits the spatio-temporal correlation among multiple measurements from different sensors. Finally, we present a new framework for data processing and describe a number of experiments under this framework. We compare our scheme with the wavelet transform and observe the effect of time stamps on the compression ratio. We report on some of the results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.5
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• pp.795-802
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• 2002

For assessing significance of a defect in a component operating at high (creeping) temperatures, accurate estimation of fracture mechanics parameter, $C^{*}$-integral, is essential. Although the J estimation equation in the GE/EPRl handbook can be used to estimate the $C^{*}$-integral when the creep -deformation behavior can be characterized by the power law creep, such power law creep behavior is a very poor approximation for typical creep behaviors of most materials. Accordingly there can be a significant error in the $C^{*}$-integral. To overcome problems associated with GE/EPRl approach, the reference stress approach has been proposed, but the results can be sometimes unduly conservative. In this paper, a new method to estimate the $C^{*}$-integral for deflective components is proposed. This method improves the accuracy of the reference stress approach significantly. The proposed calculations are then validated against elastic -creep finite element (FE) analyses for four different cracked geometries following various creep -deformation constitutive laws. Comparison of the FE $C^{*}$-integral values with those calculated from the proposed method shows good agreements.greements.

• ETRI Journal
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• v.42 no.4
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• pp.619-632
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• 2020

Highly dispersive S-boxes are desirable in cryptosystems as nonlinear confusion sublayers for resisting modern attacks. For a near optimal cryptosystem resistant to modern cryptanalysis, a highly nonlinear and low differential probability (DP) value is required. We propose a method based on a piecewise linear chaotic map (PWLCM) with optimization conditions. Thus, the linear propagation of information in a cryptosystem appearing as a high DP during differential cryptanalysis of an S-box is minimized. While mapping from the chaotic trajectory to integer domain, a randomness test is performed that justifies the nonlinear behavior of the highly dispersive and nonlinear chaotic S-box. The proposed scheme is vetted using well-established cryptographic performance criteria. The proposed S-box meets the cryptographic performance criteria and further minimizes the differential propagation justified by the low DP value. The suitability of the proposed S-box is also tested using an image encryption algorithm. Results show that the proposed S-box as a confusion component entails a high level of security and improves resistance against all known attacks.

• International Journal of CAD/CAM
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• v.5 no.1
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• pp.19-27
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• 2005

As three-dimensional range scanners make large point clouds a more common initial representation of real world objects, a need arises for algorithms that can efficiently process point sets. In this paper, we present a method for extracting smooth surfaces from dense point clouds. Given an unorganized set of points in space as input, our algorithm first uses principal component analysis to estimate the surface variation at each point. After defining conditions for determining the geometric compatibility of a point and a surface, we examine the points in order of increasing surface variation to find points whose neighborhoods can be closely approximated by a single surface. These neighborhoods become seed regions for region growing. The region growing step clusters points that are geometrically compatible with the approximating surface and refines the surface as the region grows to obtain the best approximation of the largest number of points. When no more points can be added to a region, the algorithm stores the extracted surface. Our algorithm works quickly with little user interaction and requires a fraction of the memory needed for a standard mesh data structure. To demonstrate its usefulness, we show results on large point clouds acquired from real-world objects.