This paper presents the performance evaluation of eight focus measure operators namely Image CURV (Curvature), GRAE (Gradient Energy), HISE (Histogram Entropy), LAPM (Modified Laplacian), LAPV (Variance of Laplacian), LAPD (Diagonal Laplacian), LAP3 (Laplacian in 3D Window) and WAVS (Sum of Wavelet Coefficients). Statistical matrics such as MSE (Mean Squared Error), PNSR (Peak Signal to Noise R...

the decisions made in the planning phase of a building project greatly affect its future operation and maintenance (o&m;) cost. recognizing the o&m; cost of condominiums’ common facilities as a critical issue for home owners, this research aims to develop an artificial neural network (ann) o&m; cost prediction model to assist developers and architects in effectively assessing the impacts of the...

We consider a simple through-the-origin linear regression example introduced by Rousseeuw, van Aelst and Hubert (1999). It is shown that the conventional least squares and least absolute error estimators converge in distribution without normalization and consequently are inconsistent. A class of weighted median regression estimators, including the maximum depth estimator of Rousseeuw and Hubert...

Kinetics and selected variables (temperature, particle size and time) for extraction of Terminalia Catappa L Kernel Oil (TCKO) were investigated using solvent extraction. Kinetic models studied were: parabolic diffusion, power law, hyperbolic, Elovich and pseudo-second-order. In ascending order, the best-fitted models at the optimum temperature and oil yield were Elovich’s model, hyperbolic...

This paper applies the recently proposed Extended Maximum Likelihood Linear Transformation (EMLLT) model in a Speaker Adaptive Training (SAT) context on the Switchboard database. Adaptation is carried out with maximum likelihood estimation of linear transforms for the means, precisions (inverse covariances) and the feature-space under the EMLLT model. This paper shows the first experimental evi...

We consider treecodes (N-body programs which use a tree data structure) from the standpoint of their worst-case behavior. That is, we derive upper bounds on the largest possible errors that are introduced into a calculation by use of various multipole acceptability criteria (MAC). We find that the conventional Barnes-Hut MAC can introduce potentially unbounded errors unless < 1=p3, and that thi...

accurate prediction of municipal solid waste’s quality and quantity is crucial for designing and programming municipal solid waste management system. but predicting the amount of generated waste is difficult task because various parameters affect it and its fluctuation is high. in this research with application of feed forward artificial neural network, an appropriate model for predicting the...

This paper derives asymptotic normality of a class of M-estimators in the generalized autoregressive conditional heteroskedastic ~GARCH! model+ The class of estimators includes least absolute deviation and Huber’s estimator in addition to the well-known quasi maximum likelihood estimator+ For some estimators, the asymptotic normality results are obtained only under the existence of fractional u...

This paper analyzes the predictive performance of standard techniques for the ‘logical analysis of data’ (LAD), within a probabilistic framework. It does so by bounding the generalization error of related polynomial threshold functions in terms of their complexity and how well they fit the training data. We also quantify the predictive accuracy in terms of the extent to which there is a large s...