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jih-1679
Boltzmann Machine Neural Network for Arabic Speech Recognition
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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   few  selected   Arabic phonemes, the results came out to be very encouragi ng .

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Psychological Speech Structure in Nahj Al-Balaghah
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The research is a contemporary stylistic study of the text that expresses the psychological
meanings in Nahj Al-Balaghah.
The research is divided to three chapters.
The first chapter : characteristics of psychological text.
It is about the power to influence the addressee ,that is to say ,the text influence power
connects with vulnerability and emotions inside the addressee spirit and his response to
violent effects shaking his feelings and that is represented in outbreaking of words vitality and
homogeneously. The Imam's wrath , grief , love to rightness , hatred of falsehood and
deviation from Islam arouses the words and emotions through :
1. Reduction in words and expansion in meaning by means of inspiration

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Publication Date
Tue Jan 03 2023
Journal Name
College Of Islamic Sciences
Arabic
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Summary
This study seeks to clarify the phenomena of polyphony, as Oswald Ducrot indicated that polyphony is an extension of linguistics, and worked to link it to vocalisation which contains vocable ends, which led Ducrot to a similar example between (speaker and vocable). He indicated that the speaker was responsible for the pronunciation In the speech, and its phenomena: dialectical denial, irony, and referral references, which came to highlight the pragmatics texts and then explain the phenomena of semantic blocks and examples in Naguib Mahfouz's novels and stories.

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Publication Date
Mon Sep 30 2019
Journal Name
College Of Islamic Sciences
Cognitive dimensions For grammar work at Sibweh In light of the data of the speech
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The Arabic grammatical theory is characterized by the characteristics that distinguish it from other languages. It is based on the following equation: In its entirety a homogeneous linguistic system that blends with the social nature of the Arab, his beliefs, and his culture.
    This means that this theory was born naturally, after the labor of maintaining an integrated inheritance, starting with its legal text (the Koran), and ends with its features of multiple attributes.
Saber was carrying the founding crucible of that theory, which takes over from his teacher, Hebron, to be built on what it has reached. It is redundant to point to his location and the status of his book.
So came to my research tagged: (c

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Publication Date
Tue Oct 01 2013
Journal Name
2013 Ieee International Conference On Systems, Man, And Cybernetics
AWSS: An Algorithm for Measuring Arabic Word Semantic Similarity
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Publication Date
Mon Jan 02 2017
Journal Name
European Journal Of Scientific Research
Fast approach for arabic text encryption using genetic algorithm
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As s widely use of exchanging private information in various communication applications, the issue to secure it became top urgent. In this research, a new approach to encrypt text message based on genetic algorithm operators has been proposed. The proposed approach follows a new algorithm of generating 8 bit chromosome to encrypt plain text after selecting randomly crossover point. The resulted child code is flipped by one bit using mutation operation. Two simulations are conducted to evaluate the performance of the proposed approach including execution time of encryption/decryption and throughput computations. Simulations results prove the robustness of the proposed approach to produce better performance for all evaluation metrics with res

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Publication Date
Wed Jun 26 2019
Journal Name
Iraqi Journal Of Science
Comprehensive Processing for Arabic Texts to Extract Their Roots
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Arabic language is a highly inflectional language where a single word can have different forms using a single root with different interpretations. Arabic does not have a standard way to find roots, the reasons for having inflectional language: suffix, prefix and infix Vowels, which built in complex processes. That is why, words require good processing for information retrieval solutions, until now, and there has been no standard approach to attaining the fully proper root. The applications on Arabic words show around 99% are derived from a combination of bilateral, Trilateral and quad lateral roots.
Processing word- stemming levels in order to extract a root is the process of removing all additional affixes. In case the process of mat

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
A Review for Arabic Sentiment Analysis Using Deep Learning
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     Sentiment Analysis is a research field that studies human opinion, sentiment, evaluation, and emotions towards entities such as products, services, organizations, events, topics, and their attributes. It is also a task of natural language processing. However, sentiment analysis research has mainly been carried out for the English language. Although the Arabic language is one of the most used languages on the Internet, only a few studies have focused on Arabic language sentiment analysis.

     In this paper, a review of the most important research works in the field of Arabic text sentiment analysis using deep learning algorithms is presented. This review illustrates the main steps used in these studies, which include

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Publication Date
Wed Feb 16 2022
Journal Name
Iraqi Journal Of Science
New Arabic Stemming based on Arabic Patterns
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Algorithms for Arabic stemming available in two main types which are root-based approach and stem-based approach. Both types have problems which have been solved in the proposed stemmer which combined rules of both main types and based on Arabic patterns (Tafealat1) to find the added letters. The proposed stemmer achieved root exploration ratio (99.08) and fault ratio (0.9).

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Publication Date
Mon Jan 30 2023
Journal Name
Iraqi Journal Of Science
Prediction of Well Logs Data and Estimation of Petrophysical Parameters of Mishrif Formation, Nasiriya Field, South of Iraq Using Artificial Neural Network (ANN)
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    Petrophysical properties including volume of shale, porosity and water saturation are significance parameters for petroleum companies in evaluating the reservoirs and determining the hydrocarbon zones. These can be achieved through conventional petrophysical calculations from the well logs data such as gamma ray, sonic, neutron, density and deep resistivity. The well logging operations of the targeted limestone Mishrif reservoirs in Ns-X Well, Nasiriya Oilfield, south of Iraq could not be done due to some problems related to the well condition. The gamma ray log was the only recorded log through the cased borehole. Therefore, evaluating the reservoirs and estimating the perforation zones has not performed and the drilled well was

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Publication Date
Tue Jun 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Application of Neural Network in the Identification of the Cumulative Production from AB unit in Main pays Reservoir of South Rumaila Oil Field.
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A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumaila Oil Field. One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells. This paper demonstrates an application of neural network with reservoir simulation technique as decision tool. A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy. Sets of available input data were collected from the exploited g

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