The atomic properties have been studied for He-like ions (He atom, Li+, Be2+ and B3+ions). These properties included, the atomic form factor f(S), electron density at the nucleus , nuclear magnetic shielding constant and diamagnetic susceptibility ,which are very important in the study of physical properties of the atoms and ions. For these purpose two types of the wave functions applied are used, the Hartree-Fock (HF) waves function (uncorrelated) and the Configuration interaction (CI) wave function (correlated). All the results and the behaviors obtained in this work have been discussed, interpreted and compared with those previously obtained.

The problem of present study is determined by answering the following questions:                                                                   

1) What is the effect of using the oral open- ended questions on Students' achievement in the third-stage of Arabic department in the college of Education? 2) What is the effect of the oral open-ended questions on developing the creative thinking of students in

This article is devoted to the cognitive study of ironic metonymy in Russian and Arabic. Metonymy and irony have traditionally been seen as parallel linguistic phenomena. But their formation and interpretation are based on different cognitive mechanisms. At the formal and functional level, metonymy and irony have a number of significant differences. Metonymy is an artistic technique, the mechanism of which is based on obvious, easily traced connections between objects and phenomena of the surrounding world. Irony is a satirical technique or a rhetorical figure that is used to create a certain artistic image, aimed at forming the hidden meaning of the statement. A native speaker intuitively feels the difference between metonymy and irony

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

Boltzmann mach ine neural network bas been used to recognize the Arabic speech.  Fast Fourier transl(>lmation algorithm has been used t() extract speciral 'features from an a caustic signal .

The  spectral  feature size is reduced by series of operations in

order to make it salable as input for a neural network which is used as a recogni zer by Boltzmann Machine Neural  network which has been used as a recognizer for phonemes . A training set consist of a number of Arabic phoneme repesentations, is used to train lhe neuntl network.

The neural network recognized Arabic. After Boltzmann Machine Neura l    network   training  the  system   with 

Cryptography is a method used to mask text based on any encryption method, and the authorized user only can decrypt and read this message. An intruder tried to attack in many manners to access the communication channel, like impersonating, non-repudiation, denial of services, modification of data, threatening confidentiality and breaking availability of services. The high electronic communications between people need to ensure that transactions remain confidential. Cryptography methods give the best solution to this problem. This paper proposed a new cryptography method based on Arabic words; this method is done based on two steps. Where the first step is binary encoding generation used t

In this work , a hybrid scheme tor Arabic speech for the recognition

of  the speaker  verification  is presented  . The scheme is hybrid as utilizes the traditional digi tal signal processi ng and neural network . Kohonen neural  network has been used as a recognizer  tor speaker verification after extract spectral  features from an acoustic signal  by Fast Fourier Transformation Algorithm(FFT) .

The system was im plemented using a PENTIUM  processor , I000

MHZ compatible and MS-dos 6.2 .

In this research study the effect of fish on the properties optical films thickness 1200-1800 and calculated energy gap Basra direct transport permitted and forbidden to membranes and urged decreasing values ??of Optical Energy Gap increase fish included accounts optical also calculate the constants visual as factories winding down and the refractive index and reflectivity membranes also by real part and imaginarythe dielectric constant