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Text Encryption Based on DNA Cryptography, RNA, and Amino Acid
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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.

Publication Date
Mon Oct 28 2019
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
Heuristic Initialization And Similarity Integration Based Model for Improving Extractive Multi-Document Summarization
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Publication Date
Tue Dec 13 2022
Journal Name
Lecture Notes In Networks And Systems
Design and FPGA Implementation of Matrix Multiplier Using DEMUX-RCA-Based Vedic Multiplier
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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Composites Science
Sawdust-Based Concrete Composite-Filled Steel Tube Beams: An Experimental and Analytical Investigation
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Incorporating waste byproducts into concrete is an innovative and promising way to minimize the environmental impact of waste material while maintaining and/or improving concrete’s mechanical characteristics and strength. The proper application of sawdust as a pozzolan in the building industry remains a significant challenge. Consequently, this study conducted an experimental evaluation of sawdust as a fill material. In particular, sawdust as a fine aggregate in concrete offers a realistic structural and economical possibility for the construction of lightweight structural systems. Failure under four-point loads was investigated for six concrete-filled steel tube (CFST) specimens. The results indicated that recycled lightweight co

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Mobile-based Telemedicine Application using SVD and F-XoR Watermarking for Medical Images
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A medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un

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Publication Date
Fri Dec 01 2023
Journal Name
Advances In Science And Technology Research Journal
Experimental Investigation and Fuzzy Based Prediction of Titanium Alloy Performance During Drilling Process
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Publication Date
Fri Dec 01 2017
Journal Name
2017 11th Asian Control Conference (ascc)
ESO-based repetitive control for rejecting periodic and aperiodic disturbances in piezoelectric actuators
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This paper presents the Extended State Observer (ESO) based repetitive control (RC) for piezoelectric actuator (PEA) based nano-positioning systems. The system stability is proved using Linear Matrix Inequalities (LMIs), which guarantees the asymptotic stability of the system. The ESObased RC used in this paper has the ability to eliminate periodic disturbances, aperiodic disturbances and model uncertainties. Moreover, ESO can be tuned using only two parameters and the model free approach of ESO-based RC, makes it an ideal solution to overcome the challenges of nano-positioning system control. Different types of periodic and aperiodic disturbances are used in simulation to demonstrate the effectiveness of the algorithm. The comparison studi

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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Synthesis and Spectroscopic Studies of some Divalent Metall Ion Complexes of 3-(4-hydroxyphenyl)-2-(3-(4-nitrobenzoyl) thioureido) propanoic acid
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Publication Date
Wed Apr 19 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Synthesis and Spectral Studies of Some Metal Complexes with Bis[O,O-2,3;O,O-5,6(Chlorocarboxylic Methyliden)] L-Ascorbic Acid
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 The reaction of L-ascorbic acid with the tirchloroacetic acid in the presence of potassium hydroxide gave new product Bis[O,O-2,3;O,O-5,6(chlorocarboxylicmethyliden)]Lascorbic acid (H2L) which was isolated and characterized by 1H,13C-NMR, elemental analysis (C,H,N), UV-Visible and Fourier Transform Infrared (FTIR). The complexes of the ligand (H2L) with metal ions, M+2= (Cu, Co, Ni, Cd and Hg) were synthesized and characterized by FTIR, UV-Visible, molar conductance, atomic absorption, magnetic susceptibility and the molar ratio. The analysis evidence showed the binding of the metal ions with (H2L) through the bicarboxylato group manner resulting in six-coordinated metal ion. The TLC for (H2L) and complexes showed one spot for eac

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Publication Date
Wed Jun 30 2010
Journal Name
Al-kindy College Medical Journal
Human Leukocyte Antigens class II influence the expression of Glutamic Acid Decarboxylase auto antibodies in Type Diabetic children and their Siblings
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Background: The immunogenetic predisposition
may be considered as an important factor for the
development of Type 1 Diabetes Mellitus (T1DM)
in association with the HLA antigens.
Objective:This study was designed to investigate
the role of HLA-class II antigens in the etiology of
type T1DM and in prediction of this disease in
siblings, and its effect on expression of glutamic
acid decarboxylase autoantibodies (GADA).
methods:Sixty children who were newly diagnosed
type 1 diabetes (diagnosed less than five months)
were selected. Their age ranged from 3-17 years.
Another 50 healthy siblings were available for this
study, their ages range from 3-16 years. Eighty
apparently healthy control subjects,

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