Research objective: This research aims to unveil how to use the method of referral in understanding the Holy Quran.
The reason for choosing the research: The one that invited me to write on this topic is the importance of the referral method, so I liked the research in it, and unveiled this wonderful Qur’anic method, so that it helps to understand the intention of God Almighty in his dear book.
The research plan: The research was divided into three topics and a conclusion.
As for the first topic, it is divided into two requirements. The first requirement deals with the definition of referral language.
In the second requirement, the referral defined convention.
As for the second topic, it deals with the types of referral, and it is divided into two requirements. The first requirement is external referral (maqam). The second requirement is internal (textual) referral.
As for the third topic, it deals with examples of referral from the Holy Qur’an, Surat Al-Anam as a model, and it is divided into two requirements, the first requirement is the definition of Surat Al-Anam. And the second requirement, in which some applications of the referral method are mentioned in Surat Al-Anam.
A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration
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This case series aims to evaluate patients affected with post COVID‐19 mucormycosis from clinical presentation to surgical and pharmacological treatment to improve the disease prognosis.
This case series was conducted at a specialized surgery hospital in Baghdad Medical City for over 10 months. Fifteen cases who had mild to severe COVID‐19 infections followed by symptoms similar to aggressive periodontitis, such as mobility and bone resorption around the multiple maxillary teeth, were included in this case series.
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In this article, a continuous terminal sliding mode control algorithm is proposed for servo motor systems. A novel full-order terminal sliding mode surface is proposed based on the bilimit homogeneous property, such that the sliding motion is finite-time stable independent of the system’s initial condition. A new continuous terminal sliding mode control algorithm is proposed to guarantee that the system states reach the sliding surface in finitetime. Not only the robustness is guaranteed by the proposed controller but also the continuity makes the control algorithm more suitable for the servo mechanical systems. Finally, a numerical example is presented to depict the advantages of the proposed control algorithm. An application in the rota
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