In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved

This paper deals with testing defected model piles in the soil in order to study their behavior. In this respect, the results of model pile tests are discussed either geotechnically or structurally according to the type of failure.   Two parameters were studied in order to evaluate the general behavior of defective piles. These parameters include the defect location and the defect type for floating and end bearing pile. The results of the experimental work indicated that the critical case for floating pile is seen to be when the defect of (5%) at the first third of the pile length at which the decrease in the bearing capacity is about (21%), while the decrease in the bearing capacity is found to be (14%) and (10%), when

This paper deals with testing defected model piles in the soil in order to study their behavior. In this respect, the results of model pile tests are discussed either geotechnically or structurally according to the type of failure.

Two parameters were studied in order to evaluate the general behavior of defective piles. These parameters include the defect location and the defect type for floating and end bearing pile. The results of the experimental work indicated that the critical case for floating pile is seen to be when the defect of (5%) at the first third of the pile length at which the decrease in the bearing capacity is about (21%), while the decrease in the bearing capacity is found to be (

Complexes ofCo(ll),Cu(||),Ni(||),pt(|| ),and pd(||) with N3O-chelating Ligand Incorporating Azo and Shiff Base Moieties ;synthesis, spectroscopic ,Thermal Decomposition Theoretical

This research is a critical methodological  study deals with some Quranic verses abrogative,abrogated.

by Ibn al-Jawzi (may Allah have mercy on him) in his book (Tafseer Zad al-Maseer) inin Surah Al-Baqara the  in the holy Quraan.

Let R be a commutative ring with non-zero identity element. For two fixed positive integers m and n. A right R-module M is called fully (m,n) -stable relative to ideal A of , if for each n-generated submodule of Mm and R-homomorphism . In this paper we give some characterization theorems and properties of fully (m,n) -stable modules relative to an ideal A of . which generalize the results of fully stable modules relative to an ideal A of R.

Allah Almighty has aggrandized the position of orphans and elevated their status in the society and has given the graces for those who sponsor the orphan and care for and protecting them, even those who rub their heads. The divine care is manifested in the verses of the Holy Bible and the Holy Quran. Therefore, the whole world cared for the orphan, and called for the rights of the orphans in the conferences and the channels. But all that was little effort that does not meet what the orphan need and some were only ink on paper that were not applied. All that mentioned above is necessary in dealing with the study (the rights of orphans in the Old Testament and Islam, a Comparative Study). The study was divided into a Preface and four inquirie

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod