This study is based on samples taken from one of the main branches of Tigris River; Gharaf River, at Kut Barrage in Wasit Governorate, Iraq. It aimes to study the quantity and quality of the mollusca Invertebrates; furthermore. The study evaluates the molluscan biodiversity of the rivers by using appropriate biodiversity indexes. Thus, the first of its kind study in the evaluation of the diversity of mollusc in Gharaf River assemblage. Monthly samples were collected randomly from the river mud, for 12 months, from January till December 2016. During the collection process; 5 stations on the river were chosen for sampling with 10(±1) Km distance between each of the stations, including Wasit Governorate. The study showed the presence of 20 Molluscs species were recorded for the first time in Gharaf River. In terms of population density, the annual average for Molluscs was 686.34 Ind./m2 . Relative Abundance Index (Ra) showed that Melanoid tuberculate, Physa acuta and Lymnaea auricularia was less abundant species in Gharaf River. According to the Constancy Index (S) Corbicula fluminalis, M. tuberculata, M. nodosa, Theodoxus jordani, L. auricularia and Physa acuta considered as constancy species in Gharaf’s environment. The highest recorded values of the Species Richness index were 0.0303, while the lowest values were a complete absence (zero). Regarding Jaccard Presence-Community, the results demonstrated that the highest similarity percentage between mollusca communities in Gharraf River was between stations 3 and 5, recorded at 66.66%. In the case of the Shannon-Weiner Diversity Index (H), the diversity values in Gharaf peaked at 7.819 bit/Ind. and a complete absence (zero) at its lowest point. However, the Species Uniformity Index (E) results revealed the highest uniformity values was 1, while, the lowest values were complete absence (zero).
Texture recognition is used in various pattern recognition applications and texture classification that possess a characteristic appearance. This research paper aims to provide an improved scheme to provide enhanced classification decisions and to decrease processing time significantly. This research studied the discriminating characteristics of textures by extracting them from various texture images using discrete Haar transform (DHT) and discrete Fourier transform DFT. Two sets of features are proposed; the first set was extracted using the traditional DFT, while the second used DHT. The features from the Fourier domain are calculated using the radial distribution of spectra, while for those extracted from Haar Wavelet the statistical
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A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro
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The aim of this paper is to estimate a single reliability system (R = P, Z > W) with a strength Z subjected to a stress W in a stress-strength model that follows a power Rayleigh distribution. It proposes, generates and examines eight methods and techniques for estimating distribution parameters and reliability functions. These methods are the maximum likelihood estimation(MLE), the exact moment estimation (EMME), the percentile estimation (PE), the least-squares estimation (LSE), the weighted least squares estimation (WLSE) and three shrinkage estimation methods (sh1) (sh2) (sh3). We also use the mean square error (MSE) Bias and the mean absolute percentage error (MAPE) to compare the estimation methods. Both theoretical c
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Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and
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Pareto distribution is used in many economic, financial and social applications. This distribution is used for the study of income and wealth and the study of settlement in cities and villages and the study of the sizes of oil wells as well as in the field of communication through the speed of downloading files from the Internet according to their sizes. This distribution is used in mechanical engineering as one of the distributions of models of failure, stress and durability. Given the practical importance of this distribution on the one hand, and the scarcity of sources and statistical research that deal with it, this research touched on some statistical characteristics such as derivation of its mathematical function , probability density
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This paper demonstrates the construction of a modern generalized Exponential Rayleigh distribution by merging two distributions with a single parameter. The "New generalized Exponential-Rayleigh distribution" specifies joining the Reliability function of exponential pdf with the Reliability function of Rayleigh pdf, and then adding a shape parameter for this distribution. Finally, the mathematical and statistical characteristics of such a distribution are accomplished
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