Several million tons of solid waste are produced each year as a result of construction and demolition activities around the world, and brick waste is one of the most widely wastes. Recently, there has been growing number in studies that conducted on using of recycling brick waste (RBW) to produce environmentally friendly concrete. The use of brick waste (BW) as potential partial cement or aggregate replacement materials is summarized in this review where the performance is discussed in the form of the mechanical strength and properties that related to durability of  concrete. It was found that, because the pozzolanic activity of clay brick powder, it can be utilized as substitute for cement in replacement level up t

Several million tons of solid waste are produced each year as a result of construction and demolition activities around the world, and brick waste is one of the most widely wastes. Recently, there has been growing number in studies that conducted on using of recycling brick waste (RBW) to produce environmentally friendly concrete. The use of brick waste (BW) as potential partial cement or aggregate replacement materials is summarized in this review where the performance is discussed in the form of the mechanical strength and properties that related to durability of  concrete. It was found that, because the pozzolanic activity of clay brick powder, it can be utilized as substitute for cement in replacement level up to 10%. Whereas,

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.

The relationships between the related parties constitute a normal feature of trading and business processes. Entities may perform parts of their activities through subsidiary entities, joint ventures and associate entities. In these cases, the entity has the ability to influence the financial and operating policies of the investee through control, joint control or significant influence,  So could affect established knowledge of transactions and balances outstanding, including commitments, and relationships with related to the evaluation of its operations by users of financial statements, including the risks and opportunities facing the entity assess the parties. So research has gained importance of the importance of the availability

This research seeks to try to address one of the important issues in society that prevents the state from achieving its social, economic, political and financial goals, represented by the low tax proceeds, through which it can achieve those goals. What is reflected on the tax proceeds, knowing that the General Tax Authority does not take into account the issue of analyzing the opportunity cost of corporate capital as one of the profit indicators when setting the annual controls, which leads to a decrease in the tax proceeds, and therefore the research objective will be to shed light on the importance of adopting the concept of analysis The opportunity cost by the General Tax Authority to achieve a tax proceeds commensurate with t

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

the power of the federal supreme court to stop the implementation of the law