Some species, such as the Eurasian Collared-Dove (S. decaocto) are fast expanding around the planet, while others, such as the European Turtle-Dove (S. turtur), are experiencing precipitous population declines. Climate change, habitat loss, greater cultivated areas, and hunting pressure are the major threats to the diversity of Streptopelia. A few species require urgent conservation action. Priority for subsequent research should be to redress outstanding taxonomic uncertainties, ascertain the effect of climate change on distributions, and put in place conservation measures for declining taxa. We provide here a detailed review on how it is possible to understand the diversity of Streptopelia and how such an understanding can con

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

Phlebotomus papatasi sand fly is the main vector of Zoonotic Cutaneous Leishmaniasis (ZCL) in Iraq. The aim of this study was to assess and predict the effects of climate change on the distribution of the cutaneous leishmaniasis (CL) cases and the main vector presently and in the future. Data of the CL cases were collected for the period (2000-2018) in addition to sand fly (SF) abundance. Geographic information system, R studio and MaxEnt (Maximum entropy niche model) software were used for analysis and predict effect of (elevation, population, Bio1-19, and Bio28-35) on CL cases distribution and SF occurrence. HadGEM2-ES model with two climate change scenarios, RCP 4.5 and RCP 8.5 were used for future projections 2050. The results showed th

   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

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

The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

 The technology in continuous and quick development, that reflects in all parts of our life and interred both scientific and practical fields. Marketing is one of them, a customer’s way to deal with choosing and demanding the product deferent from the traditional way. Some of the buying processes are electronic now, therefore the current research is identifying the digital channels that entered the world of marketing and influenced the activities and types that fall under this name and how it affects in positioning strategy, which is how to install the product or brand in the mind of the customer and was dimensions (brand identity, brand personality, brand communication, brand awareness, brand image), The researcher took t

This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different

This work was conducted to study the ability of locally prepared Zeolite NaY for the reduction of sulfur compounds from Iraqi natural gas by a continuous mode adsorption unit. Zeolite Y was hydrothermally synthesized using abundant kaolin clay as aluminum precursor. Characterization was made using chemical analysis, XRD and BET surface area. Results of the adsorption experiments showed that zeolite Y is an active adsorbent for removal H2S from natural gas and other gas streams. The effect of temperature was found inversely related to the removal efficiency. Increasing bed height was found to increase the removal efficiency at constant flow rate of natural gas. The adsorption capacity was evaluated and its maximum uptake was 5.345 mg H2S/g z

This work was conducted to study the ability of locally prepared Zeolite NaY for the reduction of sulfur compounds from Iraqi natural gas by a continuous mode adsorption unit. Zeolite Y was hydrothermally synthesized using abundant kaolin clay as aluminum precursor. Characterization was made using chemical analysis, XRD and BET surface area. Results of the adsorption experiments showed that zeolite Y is an active adsorbent for removal H2S from natural gas and other gas streams. The effect of temperature was found inversely related to the removal efficiency. Increasing bed height was found to increase the removal efficiency at constant flow rate of natural gas. The adsorption capacity was evaluated and its maximum uptake was 5.345 mg H2S/g z