In this study, Titanium Dioxide Nanoparticles were synthesized by an easy and eco-friendly technique (green synthesis) using green tea leaves (Camillia sinensis), Nanoparticles were analyzed using structural and optical analysis, the X-ray pattern showed that Titanium Dioxide NPs had a tetragonal structure with (Face Centered Tetragonal) FCT crystal structure, the UV-visible recorded an absorbance peak near 350 nm and calculated energy band gap was 3.5 eV, all measurements were proved the purity and Nano size of prepared Nanoparticles. Biochemical parameters evaluation also mentioned in this research, these analyzes showed that Titanium Dioxide nanoparticles in particular dose (50 mg/kg) have the ability to reduce blood glucose

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

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 work presents a symmetric cryptography coupled with Chaotic NN , the encryption algorithm process the data as a blocks and it consists of multilevel( coding of character, generates array of keys (weights),coding of text and chaotic NN ) , also the decryption process consists of multilevel (generates array of keys (weights),chaotic NN, decoding of text and decoding of character).Chaotic neural network is used as a part of the proposed system with modifying on it ,the keys that are used in chaotic sequence are formed by proposed key generation algorithm .The proposed algorithm appears efficiency during the execution time where it can encryption and decryption long messages by short time and small memory (chaotic NN offer capacity of m

A legal discourse in the Qur’an and Sunnah is almost devoid of the use of one of the general formulas, and due to its frequent rotation in the tongue of the legislator, the formulas may overlap their members in apparently contradictory provisions, which makes the individual from the general members appear to the beholder to be covered by two contradictory provisions, and this research came to present what might happen to him The legal text interpreter of weighting between the two opposing texts is the strength of the generality that is established by the generality formula, so the two strongest formulas in the inclusion of its members outweigh the weaker of them and precede them, and the research decided that the formulas vary

In the present study, the physical characteristics of elastomer (EL) blend with natural polymers such as polyvinyl alcohol (PVA), Dexrin (D), Arabic gum (AG), and corn starch (CS) based on high-density fiberboard wood adhesives were investigated. The EL blends were prepared by dissolving AG, D, PVA, and CS in deionized water at 70 °C for 1 h under magnetic stirring continuously until the solution was clear, and blends were made with a weight of 60/40 (w/w); then were cast into a mold with a 20 cm diameter and left at room temperature for 24 h to ensure complete water removal and drying of the samples. The prepared EL and EL blend structures, adhesion strengths, roughness, wettings, and dielectric strengths, were investigated. The modifi