We show how the first order statistic, i.e. the histogram, of the wavelet filtered image is related to the higher order statistic of the original image. We then propose a texture classification method that uses the histogram information of the filtered images as the feature vector. Classification experiments show that the proposed method achieves better classification result than the Gabor wave...

Accurate quantification of stormwater pollutant levels is essential for estimating overall contaminant discharge to receiving waters. Numerous sampling approaches exist that attempt to balance accuracy against the costs associated with the sampling method. This study employs a novel and practical approach of evaluating the accuracy of different stormwater monitoring methodologies using stormflo...

The purpose of the current paper is to propose a new model for the secondary goal in DEA by introducing secondary objective function. The proposed new model minimizes the average of the absolute deviations of data points from their median. Similar problem is studied in a related model by Liang et al. (2008), which minimizes the average of the absolute deviations of data points from their mean. ...

This work proposes a reversible data hiding algorithm that is based on the median difference histogram. The method divides the cover image into non-overlapping identical blocks. In each block, the median pixel is selected to calculate absolute differences between the median pixel value and the values of the other pixels. Then, these differences are used to generate a histogram and the histogram...

gabapentin is an anticonvulsant widely used in the treatment of epilepsy. no peculiar chromophore is available on the gabapentin moiety for direct analysis by absorption spectrophotometry. a sensitive spectrophotometric method for the determination of gabapentin in bulk, pharmaceutical formulations and human plasma has been developed. in this method, gabapentin directly derivatized with vanilli...

In classical probability and statistics, one computes many measures of interest from mean standard deviation. However, mean, especially deviation, are overly sensitive to outliers. One way address this sensitivity is by considering alternative metrics for skewness, kurtosis using absolute deviations the median (MAD). We show that proposed can be computed in terms sub-means appropriate left righ...

independence of observations is a fundamental assumption in designing an x chart for individual observations. but unfortunately, the assumption of existence of independent data is not even approximately satisfied. in fact, there is one kind of autocorrelation in the data. this paper demonstrates, through simulating an ar(1) process, that the autocorrelation in the data has deep effect on x char...

MOTIVATION Genome analysis has become one of the most important tools for understanding the complex process of cancerogenesis. With increasing resolution of CGH arrays, the demand for computationally efficient algorithms arises, which are effective in the detection of aberrations even in very noisy data. RESULTS We developed a rather simple, non-parametric technique of high computational effi...

In this paper we argue on the use of the mean absolute deviation in 1D random walk as opposed to the commonly accepted standard deviation. It presents an in detail derivation of the closed-form formula for the 1D mean absolute distance, including the proof by induction. The limit for the infinite number of steps is included.

The typical behavior of optimal solutions to portfolio optimization problems with absolute deviation and expected shortfall models using replica analysis was pioneeringly estimated by S. Ciliberti et al. [Eur. Phys. B. 57, 175 (2007)]; however, they have not yet developed an approximate derivation method for finding the optimal portfolio with respect to a given return set. In this study, an app...