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Strong Triple Data Encryption Standard Algorithm using Nth Degree Truncated Polynomial Ring Unit
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Cryptography is the process of transforming message to avoid an unauthorized access of data. One of the main problems and an important part in cryptography with secret key algorithms is key. For higher level of secure communication key plays an important role. For increasing the level of security in any communication, both parties must have a copy of the secret key which, unfortunately, is not that easy to achieve. Triple Data Encryption Standard algorithm is weak due to its weak key generation, so that key must be reconfigured to make this algorithm more secure, effective, and strong. Encryption key enhances the Triple Data Encryption Standard algorithm securities. This paper proposed a combination of two efficient encryption algorithms to satisfy the purpose of information security by adding a new level of security to Triple Data Encryption Standard algorithm using Nth Degree Truncated Polynomial Ring Unit algorithm. This aim achieved by adding two new key functions, the first one is Enckey(), and the second one is Deckey() for encryption and decryption key of Triple Data Encryption Standard to make this algorithm more stronger. The obtained results of this paper also have good resistance against brute-force attack which makes the system more effective by applying Nth Degree Truncated Polynomial Ring Unit algorithm to encrypt and decrypt key of Triple Data Encryption Standard. Also, these modifications enhance the degree of complexity, increase key search space, and make the ciphered message difficult to be cracked by the attacker.

Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
Hazard Rate Estimation Using Varying Kernel Function for Censored Data Type I
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     In this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used:  local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the

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Publication Date
Thu Jan 06 2022
Journal Name
Kuwait Journal Of Science
AVO analysis for high amplitude anomalies using 2D pre-stack seismic data
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Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the

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Publication Date
Sat Jul 01 2017
Journal Name
2017 Computing Conference
Protecting a sensitive dataset using a time based password in big data
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Publication Date
Sun Apr 01 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Hiding Data in Color Image Using Least Significant Bits of Blue Sector
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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Mining categorical Covid-19 data using chi-square and logistic regression algorithms
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Publication Date
Mon Jun 01 2026
Journal Name
Iraqi Journal For Computers And Informatics
Explainable Federated Learning for Brain Tumor Classification Using Multi-Source MRI Data
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Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings

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Publication Date
Mon Mar 01 2021
Journal Name
Journal Of Physics: Conference Series
Synthesis and characterization of some new thiazolidinone derivatives containing indole ring
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Many new heterocyclic compounds including 4-thiazolidinones containing indole with triazole units were described. The new Schiff bases [VII] a, b and [VIII] a, b synthesized by condensation acid hydrazides [II],[VI] with different (aromatic) aldehydes in absolute ethanol. The refluxing equimolar amounts of the Schiff bases ([VII] a, b,[VIII] a, b) with thioglycolic acid in benzene led to get thiazolidin-4-ones derivatives ([IX] a, b and [X] ad). Finally, the new derivatives [XI] ac run out via the reacted compound [IX] a with different n-alkyl bromide (methyl bromide, ethyl bromide, and butyl bromide)

Publication Date
Mon Mar 01 2021
Journal Name
Journal Of Physics: Conference Series
Synthesis and characterization of some new thiazolidinone derivatives containing indole ring
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Abstract<p>Many new heterocyclic compounds including 4-thiazolidinones containing indole with triazole units were described. The new Schiff bases [VII]<sub>a, b</sub> and [VIII]<sub>a,b</sub> synthesized by condensation acid hydrazides [II],[VI] with different (aromatic) aldehydes in absolute ethanol. The refluxing equimolar amounts of the Schiff bases ([VII]<sub>a,b</sub>, [VIII]<sub>a,b</sub>) with thioglycolic acid in benzene led to get thiazolidin-4-ones derivatives ([IX]<sub>a,b</sub> and [X]<sub>a-d</sub>). Finally, the new derivatives [XI]<sub>a-c</sub> run out via the reacted compound [IX]<sub>a</sub> with di</p> ... Show More
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Publication Date
Fri Dec 29 2017
Journal Name
Al-khwarizmi Engineering Journal
A Study Of Strengthening Circular Diaphragm By Ring-Shaped Concentric Ribs
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 This paper deals with the determination of stresses and deflections of clamped circular diaphragm strengthened by one or two ring-shaped concentric ribs, under uniform static and dynamic pressures. The simulation has been achieved by using the well-known engineering software finite element package MSC/NASTRAN

 As a design study, the effect of using a clamped ring, and the effect of using a ring-shaped rib on both surfaces of diaphragm instead of one, has been discussed in this work. To show the effectiveness of this study, results of this work have been compared with  published data [1].

In  the  conclusion,  the  authors underline  the  validity of  the&n

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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Using Iterative Reweighting Algorithm and Genetic Algorithm to Calculate The Estimation of The Parameters Of The Maximum Likelihood of The Skew Normal Distribution
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Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M

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