In this research we been estimated the survival function for data suffer from the disturbances and confusion of Iraq Household Socio-Economic Survey: IHSES II 2012 , to data from a five-year age groups follow the distribution of the Generalized Gamma: GG. It had been used two methods for the purposes of estimating and fitting which is the way the Principle of Maximizing Entropy: POME, and method of booting to nonparametric smoothing function for Kernel, to overcome the mathematical problems plaguing integrals contained in this distribution in particular of the integration of the incomplete gamma function, along with the use of traditional way in which is the Maximum Likelihood: ML. Where the comparison on the basis of the method of the Cen

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

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

The increasing efficiency of the telecommunications network in the city contributes to the increase in spatial interaction between activities (to influence and mutual influence) This study is based on the idea that the upgrading of telephone services provided to citizens are done exclusively through the growth and development of all levels of the service using advanced technologies to know the problems and appropriate solutions in short time and less cost. Thus, crystallized the objectives of the study which was built for the importance of GIS in the planning of services in general, and infrastructure services, in particular, including telephone services, which is represent a point of contact between individuals on the one hand a

The research aimed to investigate the level of Organizational Cynicism and Job Engagement of Government Schools teachers in Al Zubair district. To achieve this research was conducted on a random sample of (66) items. The statistical package for social sciences (SPSS) was used to analyze and examine the hypotheses. The researcher used many statistical methods to achieve the research objectives, such as simple, multi regression and the research results showed there is a significant impact to teacher's in the schools of the research sample between Organizational cynicism and Job  Engagement             

The resort to the eloquence of the poetic image as a style reveals the poet's creativity and creativity in dealing with external influences, and reflect them with emotional images express a sense of intense emotional imagination, and this imagination stems from the experience of a poetic sense of truth, tasted by the recipient before the creator of the poetic text.

In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t

Slag of aluminum is a residue which results during the melting process of primary and secondary aluminum production. Salt slag of aluminum is hazardous solid waste according to the European Catalogue for Hazardous Wastes. Hence, recovery of aluminum not only saves the environment, but also has advantages of financial and economic returns. In this research, aluminum was recovered and purified from the industrial wastes generated as waste from both of State Company for Electrical and Electronic Industries (Baghdad/AlWaziriya) and General Company for Mechanical Industries (Babylon/-Al-Escandria). It was found that these wastes contain tiny proportions of other elements such as iron, copper, nickel, titanium, lead, and potassium. Wastes were

 Prepared zeolite type A was used for theremoval of cesium ions from aqueous solution. The experimental data were analyzed by Langmuir, Freundlich isotherms. Various parameters, such as contact time, zeolite weight, pH, and initial concentration, were studied. The results indicated that the highest removal efficiency was95.53% at (2h time, 0.04 g weight, and pH=6.8). The results also showed that the Freundlic model fits well with the experimental results and is better than the Langmuir model.