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 of the intentional
meaning.
2. Consistency and coherence: illustrates the connection between words and forms of
consistency.
3. Homogeneity between the components of the sentence to illustrate the closeness and
attachment of words by formatives and grammatical links.
4. Script overlap between The Holy Quran and Nahj Al-Balaghah in those texts.
The second chapter : coherence in The Holy Quran text whether among It's words or phrases .
The most important links are : conjunctions , conductive names , linking by meaning change ,
linking by pronouns , linking by demonstrative pronouns and linking by repetition.
The third chapter : structural phenomena in psychological text which consist : elaboration and
detailing in meaning or structural expansion of the the sentences , repetition , sequence ,
diversification in syntax composition , conformity and violation. All these phenomena are
common in the texts of Nahj Al-Balaghah.
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Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq
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Speech is the first invented way of communication that human used age before the invention of writing. In this paper, proposed method for speech analyses to extract features by using multiwavelet Transform (Repeated Row Preprocessing).The proposed system depends on the Euclidian differences of the coefficients of the multiwavelet Transform to determine the beast features of speech recognition. Each sample value in the reference file is computed by taking the average value of four samples for the same data (four speakers for the same phoneme). The result of the input data to every frame value in the reference file using the Euclidian distance to determine the frame with the minimum distance is said to be the "Best Match". Simulatio
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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
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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 .