• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2000.06a
• /
• pp.1493-1510
• /
• 2000

Theoretical models that can be used to predict the range of main lobe widths and the probability distribution of the peak sidelobe levels of two-dimensionally sparse arrays are presented here. The arrays are considered to comprise microphones that are randomly positioned on a segmented grid of a given size. First, approximate expressions for the expected squared magnitude of the aperture smoothing function and the variance of the squared magnitude of the aperture smoothing function about this mean are formulated for the random arrays considered in the present study. By using the variance function, the mean value and the lower end of the range i.e., the first I percent of the mainlobe distribution can be predicted with reasonable accuracy. To predict the probability distribution of the peak sidelobe levels, distributions of levels are modeled by a Weibull distribution at each peak in the sidelobe region of the expected squared magnitude of the aperture smoothing function. The two parameters of the Weibull distribution are estimated from the means and variances of the levels at the corresponding locations. Next, the probability distribution of the peak sidelobe levels are assumed to be determined by a procedure in which the peak sidelobe level is determined as the maximum among a finite number of independent random sidelobe levels. It is found that the model obtained from the above approach predicts the probability density function of the peak sidelobe level distribution reasonably well for the various combinations of two different numbers of microphones and grid sizes tested in the present study. The application of these models to the design of random, sparse arrays having specified performance levels is also discussed.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.16 no.3
• /
• pp.152-161
• /
• 2004

Double-peak normal distribution function was suggested as the probability density function of the tidal elevation data in Korean coastal zone. Frequency distribution analysis was carried out using hourly tidal elevation data of the ten tidal gauging stations, i.e., Incheon, Kunsan, Mokpo, Cheju, Yeosu, Masan, Gadeokdo, Pusan, Pohang, and Sokcho which were served through the Internet Homepage by the National Ocean Research Institute. Based on the RMS error and $R^2$ value comparison analysis, it was found that this suggested function as the probability density function of the tidal elevation data was found to be more appropriate than the normal distribution function. The parameters of the double-peak function were estimated optimally using Levenberg-Marquardt method which was modified from the Newton method. The estimated parameters were highly correlated with the non-tidal constants of the tidal gauging stations.

• Journal of the Korean Data and Information Science Society
• /
• v.20 no.1
• /
• pp.191-202
• /
• 2009

In this study, we drive the one dimensional marginal transform function, probability density function and probability distribution function for the random variables $T_{{\xi}N}$ (Time taken by the servers during the vacations), ${\xi}_N$(Number of vacations taken by the servers) and ${\eta}_N$(Number of customers or units arrive in the system) by controlling the variability of two random variables simultaneously.

• Korean Journal of Construction Engineering and Management
• /
• v.6 no.1 s.23
• /
• pp.49-57
• /
• 2005

Construction labor productivity, which is the greatest source of variation in overall construction productivity, is the critical factor for determining the project performance in terms of time and cost, especially during scheduled overtime when extra time and cost are invested. The objective of this research is to select an appropriate type of probability distribution function representing the variability of daily labor productivity during overtime. Based on the results of statistical data analysis of labor performance during different weekly work hours, lognormal distribution is selected in order to take advantage of easiness of generating correlated random numbers. The selected lognormal distribution can be used for development of a simulation model in construction scheduling, cost analysis, and other applications areas where representation of the correlations between variables are essential.

• Computers and Concrete
• /
• v.8 no.2
• /
• pp.163-176
• /
• 2011

By virtue of chord-length density function from the field of statistical physics, this paper introduced a quantitative approach to estimate the distribution of cement paste thickness between aggregates in concrete. Dynamics mixing method based on molecular dynamics was employed to generate one model structure, then image analysis algorithm was used to obtain the distribution of thickness of cement paste in model structure for the purpose of verification. By comparison of probability density curves and cumulative probability curves of the cement paste thickness among neighboring aggregates, it is found that the theoretical results are consistent with the simulation. Furthermore, for the model mortar and concrete mixtures with practical volume fraction of Fuller-type aggregate, this analytical formula was employed to predict the influence of aggregate volume fraction and aggregate fineness. And evolution of its mean values were also investigated with the variation of volume fraction of aggregate as well as the fineness of aggregates in model mortars and concretes.

• ETRI Journal
• /
• v.32 no.6
• /
• pp.965-968
• /
• 2010

In this letter, we derive the distribution functions of five ratios involving two correlated Gaussian random variables by using the rotation of Cartesian coordinates. The results can be used in evaluating the various probability performances of wireless communications systems.

• ETRI Journal
• /
• v.33 no.3
• /
• pp.320-325
• /
• 2011

This paper considers the effects of simultaneous correlated multipath fading and shadowing on the performances of a signal-to-interference ratio (SIR)-based dual-branch selection combining (SC) diversity receiver. This analysis includes the presence of cochannel interference. A generalized fading/shadowing channel model in an interference-limited correlated fading environment is modeled by generalized-K distribution. Closed-form expressions are obtained for probability density function and cumulative distribution function of the SC output SIR, as well as for the outage probability. Based on this, the influence of various fading and shadowing parameter values and the correlation level on the outage probability is examined.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2009.09a
• /
• pp.1399-1406
• /
• 2009

Probability distribution of geotechnical properties is very useful information and it is used for evaluating the geotechnical properties itself and calculating probability of failure. In this study, probability distribution of compression index, recompression index, and void ratio are evaluated, and analysis results show that all property distributions satisfy normal and log-normal distribution.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.22 no.5
• /
• pp.607-617
• /
• 1998

Comparisons of joint probability density distribution obtained from the raw data of measured droplet sizes and velocities in a transient diesel fuel spray with computed joint probability density function were made. Simultaneous droplet sizes and velocities were obtained using PDPA. Mathematical probability density functions which can fit the experimental distributions were extracted using the principle of maximum likelihood. Through the statistical process of functions, mean droplet diameters, non-dimensional mass, momentum and kinetic energy were estimated and compared with the experimental ones. A joint log-hyperbolic density function presents quite well the experimental joint density distribution which were extracted from experimental data.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.1A
• /
• pp.31-37
• /
• 2012

The phase distribution in concrete materials strongly affects its material properties. It is important to identify the spatial distribution of void in concrete because the void in concrete materials affects mechanical behavior and permeability significantly. Therefore, a proper method to describe the void distribution of a material is needed. In this research, CT(computed tomography) is used to examine and to quantify the void distribution of porous concrete specimens. 3D concrete digital specimens are created by subsequent stacking of 2D cross-sectional images from CT. Then, probability distribution functions such as two-point correlation, lineal-path and two-point cluster functions are used for void distribution characterization. It is confirmed that probability distribution functions obtained from CT images are effective in characterizing void distributions including the anisotropy and percolation.