In this research entitled "Internal music in the poetry of guidance in the era of Islam and its artistic and semantic implications" dealt with the following:
Preface, which addressed the importance of internal music in poetry, and its close association with poetry, and the poet himself, to reveal what is touring himself and revolves in his imagination.
Repetition of all kinds: repetition of letters, repetition of words, and repetition of phrases: It showed what this repetition of strengthening the melody, and linking parts of words within the same house, or the poem, and create a special musical atmosphere to spread a certain significance and to confirm the meanings and accompanied by musical accommodation.
Anaphysics of both types: complete anaphylaxis, derivative anaphylaxis, and resulting phonological adaptation, repeated rhythm, and the formation of an image in the recipient's mind by demonstrating a certain meaning, highlighting it clearly, as well as increasing the beauty of the sound bell, and its good hearing.
Contradiction - counterpoint - and the resulting artistic images expressing the beautiful guidance of the poets of Islam, and their faith in God and the seal of his messengers, peace be upon him and his family and peace, they filmed us this guidance, which they lived, and knew beautiful.
Respond to the impotence on the chest and demonstrated its importance in internal music, as well as the added musical beauty to the house, and further strengthen its meaning.
rhyming and acceleration and explained the impact of the opening musical knows at first sight that the poet took in his poetry, and left the poets for this sometimes.
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The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
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This study shows that it is possible to fabricate and characterize green bimetallic nanoparticles using eco-friendly reduction and a capping agent, which is then used for removing the orange G dye (OG) from an aqueous solution. Characterization techniques such as scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDAX), X-Ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) were applied on the resultant bimetallic nanoparticles to ensure the size, and surface area of particles nanoparticles. The results found that the removal efficiency of OG depends on the G‑Fe/Cu‑NPs concentration (0.5-2.0 g.L-1), initial pH (2‑9), OG concentration (10-50 mg.L-1), and temperature (30-50 °C). The batch experiments showed
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The δ-mixing of γ-transitions in 70As populated in the 32 70 70 33 ( , ) Ge p n As γ
reaction is
calculated in the present work by using the a2-ratio methods. In one work we applied this method for two cases, the first one is for pure transition and the sacend one is for non pure transition, We take into account the experimental a2-coefficient for previous works and δ -values for one transition only.The results obtained are, in general, in a good agreement within associated errors, with those reported previously , the discrepancies that occur are due to inaccuracies existing in the experimental data of the previous works.
Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,
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