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Proposed Hybrid Cryptosystems Based on Modifications of Playfair Cipher and RSA Cryptosystem
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Cipher security is becoming an important step when transmitting important information through networks. The algorithms of cryptography play major roles in providing security and avoiding hacker attacks. In this work two hybrid cryptosystems have been proposed, that combine a modification of the symmetric cryptosystem Playfair cipher called the modified Playfair cipher and two modifications of the asymmetric cryptosystem RSA called the square of RSA technique and the square RSA with Chinese remainder theorem technique. The proposed hybrid cryptosystems have two layers of encryption and decryption. In the first layer the plaintext is encrypted using modified Playfair to get the cipher text, this cipher text will be encrypted using squared RSA to get the final cipher text. This algorithm achieved higher security to data but suffers from a long computational time. So Chinese remainder theorem has been used in the second hybrid cryptosystem to obtain less encryption and decryption time. The simulation results indicated that using the modified Playfair with the proposed square RSA has improved security. Moreover, using the Chinese remainder theorem achieved less encryption and decryption time in comparison to our first proposed and the standard algorithms.

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
The Effect of Electrospinning Parameters on Morphological and Mechanical Properties of PAN-based Nanofibers Membrane
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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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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Online Sumarians Cuneiform Detection Based on Symbol Structural Vector Algorithm
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The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

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Publication Date
Wed Feb 29 2012
Journal Name
Al-khwarizmi Engineering Journal
A New Audio Steganography System Based on Auto-Key Generator
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Stenography is the art of hiding the very presence of communication by embedding secret message into innocuous looking cover document, such as digital image, videos, sound files, and other computer files that contain perceptually irrelevant or redundant information as covers or carriers to hide secret messages.

In this paper, a new Least Significant Bit (LSB) nonsequential embedding technique in wave audio files is introduced. To support the immunity of proposed hiding system, and in order to recover some weak aspect inherent with the pure implementation of stego-systems, some auxiliary processes were suggested and investigated including the use of hidden text jumping process and stream ciphering algorithm. Besides, the suggested

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Wed Jun 10 2009
Journal Name
Iraqi Journal Of Laser
Simulation of passively Q-switched rate equation using saturable crystal Dy +2: CaF2 with ruby laser
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The simulation of passively Q-switching is four non – linear first order differential equations. The optimization of passively Q-switching simulation was carried out using the constrained Rosenbrock technique. The maximization option in this technique was utilized to the fourth equation as an objective function; the parameters, γa, γc and β as were dealt with as decision variables. A FORTRAN program was written to determine the optimum values of the decision variables through the simulation of the four coupled equations, for ruby laser Q–switched by Dy +2: CaF2.For different Dy +2:CaF2 molecules number, the values of decision variables was predicted using our written program. The relaxation time of Dy +2: CaF2, used with ruby was

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       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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Publication Date
Thu Aug 18 2022
Journal Name
Dental Hypotheses
Microleakage Evaluation of Glass Hybrid Restoration Following Usage of Papain-Based Gel and Ceramic Bur for Caries Removal: An in Vitro Study
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Publication Date
Mon Oct 06 2014
Journal Name
Journal Of Educational And Psychological Researches
The Effect of the Problem Based Learning on EFL Learners’ Achievement
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The present study discusses the problem based learning in Iraqi classroom. This method aims to involve all learners in collaborative activities and it is learner-centered method. To fulfill the aims and verify the hypothesis which reads as follow” It is hypothesized that there is no statistically significant differences between the achievements of Experimental group and control group”. Thirty learners are selected to be the sample of present study.Mann-Whitney Test for two independent samples is used to analysis the results. The analysis shows that experimental group’s members who are taught according to problem based learning gets higher scores than the control group’s members who are taught according to traditional method. This

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Publication Date
Sun Jan 04 2015
Journal Name
Journal Of Educational And Psychological Researches
The Effect of the Problem Based Learning on EFL Learners’ Achievement
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The present study discusses the problem based learning in Iraqi classroom. This method aims to involve all learners in collaborative activities and it is learner-centered method. To fulfill the aims and verify the hypothesis which reads as follow” It is hypothesized that there is no statistically significant differences between the achievements of Experimental group and control group”. Thirty learners are selected to be the sample of present study.Mann-Whitney Test for two independent samples is used to analysis the results. The analysis shows that experimental group’s members who are taught according to problem based learning gets higher scores than the control group’s members who are taught according to traditional method. This

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Publication Date
Mon May 27 2019
Journal Name
Al-khwarizmi Engineering Journal
Investigation the Influence of SPIF Parameters on Residual Stresses for Angular Surfaces Based on Iso-Planar Tool Path
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Incremental Sheet Metal Forming (ISMF) is a modern sheet metal forming technology which offers the possibility of manufacturing 3D complex parts of thin sheet metals using the CNC milling machine. The surface quality is a very important aspect in any manufacturing process. Therefore, this study focuses on the resultant residual stresses by forming parameters, namely; (tool shape, step over, feed rate, and slope angle) using Taguchi method for the products formed by single point incremental forming process (SPIF). For evaluating the surface quality, practical experiments to produce pyramid like shape have been implemented on aluminum sheets (AA1050) for thickness (0.9) mm. Three types of tool shape used in this work, the spherical tool ga

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