The article is devoted to the Russian-Arabic translation, a particular theory of which has not been developed in domestic translation studies to the extent that the mechanisms of translation from and into European languages are described. In this regard, as well as with the growing volumes of Russian-Arabic translation, the issues of this private theory of translation require significant additions and new approaches. The authors set the task of determining the means of translation (cognitive and mental operations and language transformations) that contribute to the achievement of the most equivalent correspondences of such typologically different languages as Russian and Arabic. The work summarizes and analyzes the accumulated experience of modern Russian linguists, Arabists (Belkin V.M., Gabuchan G.M., Grande B.M., Finkelberg N.D., Frolov V.D., etc.) and representatives of the Arabic classical linguistic school (Ibn Jinni, Sibawayh, etc.) in determining the carrier of word-formation meaning. The purpose of the study is designated as the description of the role of this category in achieving equivalence in the pair of Russian and Arabic. The lexical-semantic group of tools and instruments was considered as a material. These lexemes, both in Russian and Arabic, have an acceptable frequency, cover various stylistic registers and are formed by a relatively limited set of formants, interlingual correspondences of which can be established and compared. For the first time, on the material of this lexico-semantic group, a systemic interlingual correlation of the series of word-building formants in Russian and Arabic is revealed. The authors draw conclusions about the category of the word-formation model as a key one in the algorithm of translation activity, as well as about the specific linguistic signs of the equivalence of the Arabic-Russian translation (full transfer of the real meaning of the motivating base, the coincidence of the rhythm of the derived Arabic word with a model, the correspondence of the derivative to the grammatical categories contained in the model).
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
... Show MoreCryptography 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
... Show MoreBoltzmann 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
... Show MoreSentiment 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
... Show MoreIn 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 .
Deaf and dumb peoples are suffering difficulties most of the time in communicating with society. They use sign language to communicate with each other and with normal people. But Normal people find it more difficult to understand the sign language and gestures made by deaf and dumb people. Therefore, many techniques have been employed to tackle this problem by converting the sign language to a text or a voice and vice versa. In recent years, research has progressed steadily in regard to the use of computers to recognize and translate the sign language. This paper reviews significant projects in the field beginning with important steps of sign language translation. These projects can b
The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T
Gum Arabic is a natural gummy exudate gained from the trees of Acacia species (Acacia senegal and Acacia seyal), Family: Fabaceae. Gum Arabic considers as a dietary fiber with a high percentage of carbohydrates and low protein content. Sugars arabinose and ribose were originally discovered and isolated from gum Arabic and it is representing the original source of these sugars. A gum emanation from trees occurs under stress conditions such as heat, poor soil fertility, drought, and injury. Mainly gum is produced in belt region of Africa, mainly Sudan, Chad, and Nigeria. In the food industry, it is used in confectionery; in the pharmaceutical industry, it is used as emulsifier, film coating and others. Traditionally the g
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