The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

Cryptography algorithms play a critical role in information technology against various attacks witnessed in the digital era. Many studies and algorithms are done to achieve security issues for information systems. The high complexity of computational operations characterizes the traditional cryptography algorithms. On the other hand, lightweight algorithms are the way to solve most of the security issues that encounter applying traditional cryptography in constrained devices. However, a symmetric cipher is widely applied for ensuring the security of data communication in constraint devices. In this study, we proposed a hybrid algorithm based on two cryptography algorithms PRESENT and Salsa20. Also, a 2D logistic map of a chaotic system is a

This work presents the use of laser diode in the fiber distributed data interface FDDI networks. FDDI uses optical fiber as a transmission media. This solves the problems resulted from the EMI, and noise. In addition it increases the security of transmission. A network with a ring topology consists of three computers was designed and implemented. The timed token protocol was used to achieve and control the process of communication over the ring. Nonreturn to zero inversion (NRZI) modulation was carried out as a part of the physical (PHY) sublayer. The optical system consists of a laser diode with wavelength of 820 nm and 2.5 mW maximum output power as a source, optical fiber as a channel, and positive intrinsic negative (PIN) photodiode

New hydrazone derivatives of Fenoprofen were synthesized and evaluated for their anti-inflammatory activity by means of egg white induced paw edema method. All the synthesized target compounds were characterized by FT-IR spectroscopy, 1HNMR analysis and by measure of their physical properties. The synthesis of the target compounds(H1-H4) was accomplished by multistep reaction procedures. The synthesized target compounds were show activity in reducing paw edema thickness and their anti-inflammatory effect was comparable to that of the standard (Fenoprofen) except for compound H3 which show anti-inflammatory activity higher than Fenoprofen.

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A new series of bases of Schiff (H₂-H₄) derived from phthalic anhydrideweresynthesized. These Schiff bases were prepared by the reaction of different amines (tyrosine methyl ester, phenylalanine methyl ester, and isoniazid) with the phthalimide derived aldehyde with the aid of glacial acetic acid or triethylamine ascatalysts. All the synthesized compounds were characterized by (FT-IR and ¹HNMR) analyses and were in vitro evaluated for their antimicrobial activity against six various kinds of microorganisms. All the synthesized compounds had been screened for their antimicrobial activity against two Gram-positive bacteria “Staph. Aureus, and Bacillus subtilis

The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr

The power generation of solar photovoltaic (PV) technology is being implemented in every nation worldwide due to its environmentally clean characteristics. Therefore, PV technology is significantly growing in the present applications and usage of PV power systems. Despite the strength of the PV arrays in power systems, the arrays remain susceptible to certain faults. An effective supply requires economic returns, the security of the equipment and humans, precise fault identification, diagnosis, and interruption tools. Meanwhile, the faults in unidentified arc lead to serious fire hazards to commercial, residential, and utility-scale PV systems. To ensure secure and dependable distribution of electricity, the detection of such ha