• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.12
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• pp.12-19
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• 2014

In this paper, an advanced UWB (ultra wideband) Rake receiving technique based on the statistical distribution model is studied in the M-ary TH-PPM system with multiple access interference (MAI). In order to improve the performance of the Rake receiver, the stochastic model, which can flexibly express the behavior of MAI-plus-noise, is required and the Laplace distribution and the generalized normal Laplace (GNL) model applied by the curtosis matching method are considered. The performance of Rake receiver based on each probability distribution is evaluated in the IEEE multipath fading channel and compared to that of the conventional Rake receiver. The suggested approach shows a superior BER performance than that of conventional Rake receiver.

• Wind and Structures
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• v.34 no.5
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• pp.421-435
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• 2022

To investigate the non-Gaussian properties of fluctuating wind pressures and the error margin of extreme wind loads on a long-span curved roof with matching and mismatching ratios of turbulence integral scales to depth (L_u^x/D), a series of synchronized pressure tests on the rigid model of the complex curved roof were conducted. The regions of Gaussian distribution and non-Gaussian distribution were identified by two criteria, which were based on the cumulative probabilities of higher-order statistical moments (skewness and kurtosis coefficients, S_k and K_u) and spatial correlation of fluctuating wind pressures, respectively. Then the characteristics of fluctuating wind-loads in the non-Gaussian region were analyzed in detail in order to understand the effects of turbulence integral-scale. Results showed that the fluctuating pressures with obvious negative-skewness appear in the area near the leading edge, which is categorized as the non-Gaussian region by both two identification criteria. Comparing with those in the wind field with matching L_u^x/D, the range of non-Gaussian region almost unchanged with a smaller L_u^x/D, while the non-Gaussian features become more evident, leading to higher values of S_k, Ku and peak factor. On contrary, the values of fluctuating pressures become lower in the wind field with a smaller L_u^x/D, eventually resulting in underestimation of extreme wind loads. Hence, the matching relationship of turbulence integral scale to depth should be carefully considered as estimating the extreme wind loads of long-span roof by wind tunnel tests.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.3
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• pp.49-57
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• 2018

In a previous article, for analyzing a stochastic activity network, Cho proposed a method for estimating the moments (mean, variance, skewness, kurtosis) of the project completion time under the assumption that the durations of activities are independently and normally distributed. Developed in the present article is a method for estimating those moments for stochastic activity networks which allow any type of distributions for activity durations. The proposed method uses the moment matching approach to discretize the distribution function of activity duration, and then a discrete inverse-transform method to determine activity durations to be used for calculating the project completion time. The proposed method can be easily applied to large-sized activity networks, and computationally more efficient than Monte Carlo simulation, and its accuracy is comparable to that of Monte Carlo simulation.