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A Proposed Algorithm for Encrypted Data Hiding in Video Stream Based on Frame Random Distribution
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     The science of information security has become a concern of many researchers, whose efforts are trying to come up with solutions and technologies that ensure the transfer of information in a more secure manner through the network, especially the Internet, without any penetration of that information, given the risk of digital data being sent between the two parties through an insecure channel. This paper includes two data protection techniques. The first technique is cryptography by using Menezes Vanstone elliptic curve ciphering system, which depends on public key technologies. Then, the encoded data is randomly included in the frame, depending on the seed used. The experimental results, using a PSNR within average of 65 and MSE within average of 85, indicate that the proposed method has proven successful in its ability to efficiently embedding data.

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Publication Date
Mon Jan 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On Estimation of P(Y<X) in Case Inverse Kumaraswamy Distribution
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The estimation of the stressÙ€ strength reliability of Invers Kumaraswamy distribution will be introduced in this paper based on the maximum likelihood, moment and shrinkage methods. The mean squared error has been used to compare among proposed estimators. Also a Monte Carlo simulation study is conducted to investigate the performance of the proposed methods in this paper.

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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
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Fuzzy Based Clustering for Grayscale Image Steganalysis
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Fuzzy Based Clustering for Grayscale Image Steganalysis

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Investigation of Load and Pressure Distribution on Wing with Wake Rollup for Low Speed Aircraft
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The presented work shows a preliminary analytic method for estimation of load and pressure distributions on low speed wings with flow separation and wake rollup phenomena’s. A higher order vortex panel method is coupled with the numerical lifting line theory by means of iterative procedure including models of separation and wake rollup. The computer programs are written in FORTRAN which are stable and efficient.

      The capability of the present method is investigated through a number of test cases with different types of wing sections (NACA 0012 and GA(W)-1) for different aspect ratios and angles of attack, the results include the lift and drag curves, lift and pressure distributions along the wing s

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Publication Date
Mon Apr 03 2023
Journal Name
Aro-the Scientific Journal Of Koya University
The Most Common Characteristics of Fragile Video Watermarking
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The progress of network and multimedia technologies has been phenomenal during the previous two decades. Unauthorized users will be able to copy, retransmit, modify reproduction, and upload the contents more easily as a result of this innovation. Malicious attackers are quite concerned about the development and widespread use of digital video. Digital watermarking technology gives solutions to the aforementioned problems. Watermarking methods can alleviate these issues by embedding a secret watermark in the original host data, allowing the genuine user or file owner to identify any manipulation. In this study, lots of papers have been analyzed and studied carefully, in the period 2011–2022. The historical basis of the subject shou

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Comparing the Random Forest vs. Extreme Gradient Boosting using Cuckoo Search Optimizer for Detecting Arabic Cyberbullying
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   Cyberbullying is one of the major electronic problems, and it is not a new phenomenon. It was present in the traditional form before the emergence of social networks, and cyberbullying has many consequences, including emotional and physiological states such as depression and anxiety. Given the prevalence of this phenomenon and the importance of the topic in society and its negative impact on all age groups, especially adolescents, this work aims to build a model that detects cyberbullying in the comments on social media (Twitter) written in the Arabic language using Extreme Gradient Boosting (XGBoost) and Random Forest methods in building the models. After a series of pre-processing, we found that the accuracy of classification of t

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Review of Challenges and Solutions for Genomic Data Privacy-Preserving
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     The dramatic decrease in the cost of genome sequencing over the last two decades has led to an abundance of genomic data. This data has been used in research related to the discovery of genetic diseases and the production of medicines. At the same time, the huge space for storing the genome (2–3 GB) has led to it being considered one of the most important sources of big data, which has prompted research centers concerned with genetic research to take advantage of the cloud and its services in storing and managing this data. The cloud is a shared storage environment, which makes data stored in it vulnerable to unwanted tampering or disclosure. This leads to serious concerns about securing such data from tampering and unauthoriz

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Publication Date
Wed May 25 2022
Journal Name
Iraqi Journal Of Science
Developing a Heuristic Algorithm to Solve Uncertainty Problem of Resource Allocation in a Software Project Scheduling
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     In project management process, the objective is to define and develop a model for planning, scheduling, controlling, and monitoring different activities of a particular project. Time scheduling plays an important role in successful implementation of various activities and general outcome of project. In practice, various factors cause projects to suffer from time delay in accomplishing the activities. One important reason is imprecise knowledge about time duration of activities. This study addresses the problem of project scheduling in uncertain resource environments, which are defined by uncertain activity durations.  The study presents a solution of the levelling and allocation problems for projects that have some uncertain ac

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Publication Date
Tue Aug 31 2021
Journal Name
Iraqi Journal Of Science
Application of Neural Network Analysis for Seismic Data to Differentiate Reservoir Units of Yamama Formation in Nasiriya Oilfield A Case Study in Southern Iraq
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      The EMERGE application from Hampsson-Russell suite programs was used in the present study. It is an interesting domain for seismic attributes that predict some of reservoir three dimensional or two dimensional properties, as well as their combination. The objective of this study is to differentiate reservoir/non reservoir units with well data in the Yamama Formation by using seismic tools. P-impedance volume (density x velocity of P-wave) was used in this research to  perform a three dimensional seismic model on the oilfield of Nasiriya by using post-stack data of  5 wells. The data (training and application) were utilized in the EMERGE analysis for estimating the reservoir properties of P-wave ve

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Publication Date
Thu Jul 01 2021
Journal Name
Iraqi Journal Of Science
Meerkat Clan Algorithm for Solving N-Queen Problems
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The swarm intelligence and evolutionary methods are commonly utilized by researchers in solving the difficult combinatorial and Non-Deterministic Polynomial (NP) problems. The N-Queen problem can be defined as a combinatorial problem that became intractable for the large ‘n’ values and, thereby, it is placed in the NP class of problems. In the present study, a solution is suggested for the N-Queen problem, on the basis of the Meerkat Clan Algorithm (MCA). The problem of n-Queen can be mainly defined as one of the generalized 8-Queen problem forms, for which the aim is placing 8 queens in a way that none of the queens has the ability of killing the others with the use of the standard moves of the chess queen. The Meerkat Clan environm

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