This research highlights one of the most important issues that have been controversial between Islamic schools, which is the duality of Intellect  and Revelation and the nature of their relationship, in two core points:

The first point: Could there be a real conflict between Intellect  and revelation? While the school of hadith view that this assumption is a rational assumption that does not real as long as the revelation is correct and the Intellect  is clear, and that what is claimed are due to other Intellect s, we find that the Ash’ari school adopts the saying that the real conflict may occur, but rather confirms its occurrence.

The second point: For whom is the priority, for the Intellect  or th

Sewage pumping stations are considered an important part of any sewerage system. Pumps failure in these stations means that the pumps are unable to work at the design requirement (flow capacity and head) and that may cause sewer overflow and flooding leading to sewer deterioration. In this paper, two main sewage pumping stations in Baghdad city were selected as case studies, Al- Habibia and Al-Ghazali located on Zublin trunk sewer 3000 mm and Baghdad trunk sewer 1200-2100 respectively. This study focused mainly on the operation of main sewage pumping stations and their effect, both directly and indirectly, on changing hydraulic properties, which leads to an increase in the deterioration of sewage pipes. The hydraulic analysis was co

The present study experimentally and numerically investigated the impact behavior of composite reinforced concrete (RC) beams with the pultruded I-GFRP and I-steel beams. Eight specimens of two groups were cast in different configurations. The first group consisted of four specimens and was tested under static load to provide reference results for the second group. The four specimens in the second group were tested first under impact loading and then static loading to determine the residual static strengths of the impacted specimens. The test variables considered the type of encased I-section (steel and GFRP), presence of shear connectors, and drop height during impact tests. A mass of 42.5 kg was dropped on the top surface at the m

تكمن أهمية البحث من الاستفادة من تمرينات الخاصة بمساعدة استعمال أي جهاز تدريبي مثل استعمال جهاز (Vertimax) فإِنَّ هذهِ التدريبات تساعد في تطوير التحمل الخاص وفقًا لما يتطور من قدرات بدنية باستعمال هذا الجهاز، ومن هنا برزت مشكلة البحث انه من المهم  للاعب ان يعمل على الروافع الجسم للحصول على اداء افضل في عملية الرمي والحصول على افضل انجاز لهذة الفعالية باستعمال جهاز تدريبي جديد حيث يسلط مقاومات متعددة في ان وا

     The aim of this paper is to study the nonlinear delay second order eigenvalue problems which consists of delay ordinary differential equations, in fact one of the expansion methods that is called the least square method which will be developed to solve this kind of problems.

 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

  Computer software is frequently used for medical decision support systems in different areas. Magnetic Resonance Images (MRI) are widely used images for brain classification issue. This paper presents an improved method for brain classification of MRI images. The proposed method contains three phases, which are, feature extraction, dimensionality reduction, and an improved classification technique. In the first phase, the features of MRI images are obtained by discrete wavelet transform (DWT). In the second phase, the features of MRI images have been reduced, using principal component analysis (PCA). In the last (third) stage, an improved classifier is developed. In the proposed classifier, Dragonfly algorithm is used instead