A New Approach for Dispersion Parameters

This paper presents a new approach to identify and estimate the dispersion parameters for bivariate, trivariate and multivariate correlated binary data, not only with scalar value but also with matrix values. For this direction, we present some recent studies indicating the impact of over-dispersion on the univariate data analysis and comparing a new approach with these studies. Following the property of McCullagh and Nelder [1] for identifying dispersion parameter in univariate case, we extended this property to analyze the correlated binary data in higher cases. Finally, we used these estimates to modify the correlated binary data, to decrease its over-dispersion, using the Hunua Ranges data as an ecology problem.

Sequential Parameter Estimation Using Modal Dispersion Curves in Shallow Water

Existing sequential parameter estimation methods use the acoustic pressure of a line array as observations. The modal dispersion curves are employed to estimate the sound speed profile（SSP） and geoacoustic parameters based on the ensemble Kalman filter. The warping transform is implemented to the signals received by a single hydrophone to obtain the dispersion curves. The experimental data are collected at a range-independent shallow water site in the South China Sea. The results indicate that the SSPs are well estimated and the geoacoustic parameters are also well determined. Comparisons of the observed and estimated modal dispersion curves show good agreement.

Experimental Study on Dispersion of Unconfined Aquifer in a Site of Jilin City

Dispersion parameter is an important parameter for the establishment of groundwater solute transport model.The dispersion test uses sodium chloride as a tracer,which was conducted in a site in Jilin City.The standard curve comparison method was used to solve the dispersion parameters of the aquifer under the natural flow field.The test results show that under the natural flow field,the longitudinal dispersion of unconfined aquifer in Jilin City is 0.400m,and the transverse dispersion is 1.933×10-5~6.557×10-3m;while the longitudinal dispersion coefficient is 0.246m2/d,the transverse dispersion coefficient is 1.191×10-5~4.039×10-3m2/d.The above results can provide an important parameter basis for the establishment of groundwater solute transport model,the accurate prediction of temporal and spatial variation of pollutant concentration in groundwater and the formulation of groundwater pollution prevention and control scheme.

Structural,optical and dielectric investigations on RECr_(0.85)Mn_(0.15)O_(3)(RE=Ho,Gd and Pr) nanoparticles

We hereby report the room-temperature structural and optical characterization of RECr_(0.85)Mn_(0.15)O_(3)(RECMO,RE=Ho,Gd and Pr) compounds synthesized by the auto-combustion sol-gel route.Their low temperature dielectric properties are also presented.The RECMO compounds crystallize in an orthorhombic Pbnm symmetry with an average grain size range of 51-80 nm.Structural analysis reveals an increase in the structural distortion compared to that of the undoped bulk compounds.Optical measurements exhibit a significant reduction in bandgap values for RECMO nanoparticles when compared with their undoped bulk compounds.Further,from the absorbance measurements various optical parameters such as skin depth,extinction coefficient,refractive index and optical conductivity were also calculated.The dielectric analysis confirms the lower values of the dielectric permittivity and dielectric loss than those of their corresponding bulk compounds.AC conductivity versus frequency and temperature data are fitted according to the Jonscher's power law and Arrhenius law,respectively.The small polaron hopping is responsible for the electric conduction in these compounds.The tunability of the optical and dielectric properties as a result of substitution and particle size reduction makes these materials useful for various potential applications in photocatalysis,optoelectronics and low permittivity dielectrics.

Path sets size,model specification,or model estimation:Which one matters most in predicting stochastic user equilibrium traffic flow?

This study aims to make an objective comparative analysis between the relative significance of three crucial modelling aspects involved in the probabilistic analysis of transport networks. The first question to address is the extent to which the size of generated path sets can affect the prediction of the static flow in the path-based traffic assignment paradigm. The importance of this question arises from the fact that the need to generate a large quantity of paths may be perceived by analysts as a preventative reason as to the application of path-based stochastic traffic assignment （STA） models for large-scale networks. A simulated path generation algorithm, which allows the number of generated paths to be under modeller＇s control, is applied. Findings show that the size of the generated path sets does not substantially affect the flow prediction outcome in this case study. Further investigations with respect to the relative importance of STA model estimation （or equivalently, parameter calibration） and model specification （or equivalently, error term formulation） are also conducted. A paired combinatorial logit （PCL） assignment model with an origin-destination-specific-parameter, along with a heuristic method of model estimation （calibration）, is proposed. The proposed model cannot only accommodate the correlation between path utilities, but also accounts for the fact that travelling between different origin-destination （O-D） pairs can correspond to different levels of stochasticity and choice randomness. Results suggest that the estimation of the stochastic user equilibrium （SUE） models can affect the outcome of the flow prediction far more meaningfuUy than the complexitv of the choice model （i.e.. model specification）.