Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

This research is a comparative jurisprudential study that focuses on Imam Al-Bayhaqi’s preferred opinions in his book Al-Khilafiyat (The Disagreements), the part of Al-Rida’a (Breastfeeding). It is considered one of the most important familial topics that is concerned with organizing the social relations in Islam, strengthens the family ties and that prevents the family disintegration due to the ignorance and lack in comprehending Sharia laws (Islam law) in all aspects. The study follows the inductive and descriptive method. It aims at examining the prohibition of marriage when breastfeeding takes place at the time of woman’s conversion to Islam or during her infidelity period. It further aims at verifying the prohibition

The purpose of this paper is to find the best multiplier approximation of unbounded functions in    –space by using some discrete linear positive operators. Also we will estimate the degree of the best multiplier approximation in term of modulus of continuity and the averaged modulus.

KE Sharquie, HR Al-Hamamy, AA Noaimi, KA Ali, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 3

In this work, solid random gain media were fabricated from laser dye solutions containing nanoparticles as scattering centers. Two different rhodamine dyes (123 and 6G) were used to host the highly-pure titanium dioxide nanoparticles to form the random gain media. The spectroscopic characteristics (mainly fluorescence) of these media were determined and studied. These random gain media showed laser emission in the visible region of electromagnetic spectrum. Fluorescence characteristics can be controlled to few nanometers by adjusting the characteristics of the host and nanoparticles as well as the preparation conditions of the samples. Emission of narrow linewidth (3nm) and high intensity in the visible region (533-537nm) was obtained.

This study presents a detailed morphology and taxonomic study of Polysiphonia subtilissima collected from Abdul Rehman Goth, Karachi coast, Pakistan. Polysiphonia is a filamentous heterotrichous red algae, characterized by its branching structures and attachment mechanisms. P. subtilissima is notable for its broad salinity tolerance and wide distribution across marine and freshwater ecosystems. This research provides an in-depth examination of the internal and external structures of P. subtilissima, contributing to its systematic study and documenting its first recorded occurrence in Pakistani coastal areas, bordering the northern Arabian Sea. The findings enhance the understanding of the species taxonomy and its ecological role in

The aim of this study is to describe the leech species that are used in some of the alternative medicine clinics in Baghdad Province based on morphometric measurements and colouring pattern of the body. A collection of twenty leeches was provided from some clinics. All specimens were identified and described based on standard available keys. The morphometric characteristics and colouring patterns were recorded and the indicated that these leeches were Hirudo orientalis Utevsky & Trontelj, 2005 and H. verbana Carena, 1820.

Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate