To achieve safe security to transfer data from the sender to receiver, cryptography is one way that is used for such purposes. However, to increase the level of data security, DNA as a new term was introduced to cryptography. The DNA can be easily used to store and transfer the data, and it becomes an effective procedure for such aims and used to implement the computation. A new cryptography system is proposed, consisting of two phases: the encryption phase and the decryption phase. The encryption phase includes six steps, starting by converting plaintext to their equivalent ASCII values and converting them to binary values. After that, the binary values are converted to DNA characters and then converted to their equivalent complementary DNA sequences. These DNA sequences are converted to RNA sequences. Finally, the RNA sequences are converted to the amino acid, where this sequence is considered as ciphertext to be sent to the receiver. The decryption phase also includes six steps, which are the same encryption steps but in reverse order. It starts with converting amino acid to RNA sequences, then converting RNA sequences to DNA sequences and converting them to their equivalent complementary DNA. After that, DNA sequences are converted to binary values and to their equivalent ASCII values. The final step is converting ASCII values to alphabet characters that are considered plaintext. For evaluation purposes, six text files with different sizes have been used as a test material. Performance evaluation is calculated based on encryption time and decryption time. The achieved results are considered as good and fast, where the encryption and decryption times needed for a file with size of 1k are equal to 2.578 ms and 2.625 ms respectively, while the encryption and decryption times for a file with size of 20k are equal to 268.422 ms and 245.469 ms respectively.
In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
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Symmetric cryptography forms the backbone of secure data communication and storage by relying on the strength and randomness of cryptographic keys. This increases complexity, enhances cryptographic systems' overall robustness, and is immune to various attacks. The present work proposes a hybrid model based on the Latin square matrix (LSM) and subtractive random number generator (SRNG) algorithms for producing random keys. The hybrid model enhances the security of the cipher key against different attacks and increases the degree of diffusion. Different key lengths can also be generated based on the algorithm without compromising security. It comprises two phases. The first phase generates a seed value that depends on producing a rand
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The electrospun nanofibers membranes (ENMs) have gained great attention due to their superior performance. However, the low mechanical strength of ENMs, such as the rigidity and low strength, limits their applications in many aspects which need adequate strength, such as water filtration. This work investigates the impact of electrospinning parameters on the properties of ENMs fabricated from polyacrylonitrile (PAN) solved in N, N-Dimethylformamide (DMF). The studied electrospinning parameters were polymer concentration, solution flow rate, collector rotating speed, and the distance between the needle and collector. The fabricated ENMs were characterized using scanning electron microscopy (SEM) to understand the surface morphology and es
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Background: Oral Lichen planus (OLP) is a T-cell mediated chronic inflammatory oral mucosal disease of unknown etiology. Recent studies have reported an increased oxidative stress and lipid peroxidation in such patients. This suggests that reactive oxygen species may have a role in the pathogenesis of lichen planus. Oxidative stress in OLP release molecules consisting of granzymes resulting in local tissue damage in the effectors. Antioxidants that can defend against oxidative stress in the body cells include enzymes, as well as non- enzymatic antioxidants, such as melatonin, uric acid, vitamin A and E. Purpose: To study the level of salivary vitamin E and uric acid as antioxidant agents in patients with OLP and compared with healthy con
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SYNTHESIS, CHARACTERIZATION, STRUCTURAL, THERMAL, POM STUDIES, ANTIMICROBIAL AND DNA CLEAVAGE ACTIVITY OF A NEW SCHIFF BASE-AZO LIGAND AND ITS COMPLEXATION WITH SELECTED METAL IONS
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RKRAS L. K. Abdul Karem, F. H. Ganim, Biochemical and Cellular Archives, 2018 - Cited by 2
The light-based life in the universe, including the human derived concepts and meanings of the fear of darkness and evil, comfort and goodness of light, became constitute bilateral haunted man to this day in various concepts of life.Therefore reflect the light form artistic aesthetic in visual arts such arts Fine Photography and the other until the emergence of art cinema, as the use of lighting in cinema has produced high-energy in the composition of its values expressive and symbolic, where it became dark and light are the space visually moving the vehicles media kit for many within the work structure artwork. The research is divided into five chapters, the first chapter (the methodological framework) that included an introduction the
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