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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
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Compared with Genetic Algorithm Fast – MCD – Nested Extension and Neural Network Multilayer Back propagation
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The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu

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Publication Date
Wed Nov 16 2016
Journal Name
Eurasip Journal On Wireless Communications And Networking
Evaluation of efficient vehicular ad hoc networks based on a maximum distance routing algorithm
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Traffic management at road intersections is a complex requirement that has been an important topic of research and discussion. Solutions have been primarily focused on using vehicular ad hoc networks (VANETs). Key issues in VANETs are high mobility, restriction of road setup, frequent topology variations, failed network links, and timely communication of data, which make the routing of packets to a particular destination problematic. To address these issues, a new dependable routing algorithm is proposed, which utilizes a wireless communication system between vehicles in urban vehicular networks. This routing is position-based, known as the maximum distance on-demand routing algorithm (MDORA). It aims to find an optimal route on a hop-by-ho

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Diversity Operators-based Artificial Fish Swarm Algorithm to Solve Flexible Job Shop Scheduling Problem
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Artificial fish swarm algorithm (AFSA) is one of the critical swarm intelligent algorithms. In this
paper, the authors decide to enhance AFSA via diversity operators (AFSA-DO). The diversity operators will
be producing more diverse solutions for AFSA to obtain reasonable resolutions. AFSA-DO has been used to
solve flexible job shop scheduling problems (FJSSP). However, the FJSSP is a significant problem in the
domain of optimization and operation research. Several research papers dealt with methods of solving this
issue, including forms of intelligence of the swarms. In this paper, a set of FJSSP target samples are tested
employing the improved algorithm to confirm its effectiveness and evaluate its ex

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
The awareness degree of teacher students in Arabic language department and their supervisors at Al-aqsa University for their future role in knowledge age
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The study aimed to identify the awareness degree of teacher students in the department of Arabic language and their supervisors at Al-aqsa University for their future roles in the age of knowledge. To achieve this objective, descriptive- analytical approach was used. The instruments of this study were two questionnaires: first one consist of (20) item for teacher students, and the second consist of (27) item for educational supervisors which covered three roles: professional, technological, and humanitarian. The sample was (120) student selected randomly, and (39) supervisors of Arabic language. The result revealed that the mean of degree awareness of teacher students and their supervisors of future role are (3.857), (3.472) respectively

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Publication Date
Mon Apr 04 2022
Journal Name
Journal Of Educational And Psychological Researches
The Degree of Availability of the Dimensions of Organizational Immunity Systems t the University of Tabuk in KSA from the Perspectives of Academic Leaders
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This study aims to investigate the academic leaders’ perceptions towards the degree of availability of the dimensions of organizational immunity systems at the University of Tabuk, as well as to reveal the statistically significant differences between the average responses of the study sample members about the degree of availability of these dimensions at their university due to the variables of (gender, leadership position, and college specialization). To achieve the objectives of the study, a descriptive survey method was used. The study population consisted of (200) male and female leaders who were academic leaders at the University of Tabuk. A questionnaire was used as a tool for collecting data, which its validity and reliability

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Publication Date
Sun Jun 30 2019
Journal Name
Journal Of The College Of Education For Women
The Degree of Practicing of the Sixth Primary Social Studies’ Teachers in Iraq for the Principles of Active Learning from their Point of view
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This study aimed to explore The Degree of Practicing of the Sixth Primary Social Studies’ Teachers in Iraq for the Principles of Active Learning from their Point of view

The study society consisted of 230 male and femalesocial studiesteachers’ subjects for the sixth primary grade in Al-Anbar General Directorate of Education. 160 of them were selected to represent the sample of the study with a percent of (70%) from the original society. To achieve the aims of the study, the researchers prepared a questionnaire consisting of (43) items which represented the active learning principles. The validity and stability of the tool were verified. The researchers used the descriptive approach to suit the objectives of this study. &

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Publication Date
Sun Mar 28 2021
Journal Name
Journal Of The College Of Education For Women
Estimates of Palestinian University Students in Gaza Governorate to the Contribution Degree of Teaching Human Sciences in their Political Education: محمود عبد المجيد عساف
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The study aims to examine the estimation of a sample of Palestinian University students in Gaza governorate to the contribution of teaching human sciences in their political education. It further aims to reveal whether there are statistically significant differences at a significance level (α≤ 0.05) between the averages of the sample. Such differences might be attributed to the following variables: sex, residential area, specialization. To achieve this, the researcher used the descriptive approach by applying a tool of (50) items on (618) randomly chosen male and female students from the largest Palestinian universities in the governorates of Gaza. Results have shown that: the overall degree of estimation to the contribution of teachi

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Publication Date
Mon Apr 11 2011
Journal Name
Icgst
Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
A Security and Privacy Aware Computing Approach on Data Sharing in Cloud Environment
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Today, the role of cloud computing in our day-to-day lives is very prominent. The cloud computing paradigm makes it possible to provide demand-based resources. Cloud computing has changed the way that organizations manage resources due to their robustness, low cost, and pervasive nature. Data security is usually realized using different methods such as encryption. However, the privacy of data is another important challenge that should be considered when transporting, storing, and analyzing data in the public cloud. In this paper, a new method is proposed to track malicious users who use their private key to decrypt data in a system, share it with others and cause system information leakage. Security policies are also considered to be int

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Scopus (4)
Crossref (1)
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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Semi parametric Estimators for Quantile Model via LASSO and SCAD with Missing Data
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In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

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