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bsj-5112
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
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Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus, the exact way by which the network will hide the information is unable to be known to anyone who does not have the weights.  The second goal is to increase hiding capacity, which has been achieved by using CNN as a strategy to make decisions to determine the best areas that are redundant and, as a result, gain more size to be hidden. Furthermore, In the proposed model, CNN is concurrently trained to generate the revealing and hiding processes, and it is designed to work as a pair mainly. This model has a good strategy for the patterns of images, which assists to make decisions to determine which is the parts of the cover image should be redundant, as well as more pixels are hidden there. The CNN implementation can be done by using Keras, along with tensor flow backend. In addition, random RGB images from the "ImageNet dataset" have been used for training the proposed model (About 45000 images of size (256x256)). The proposed model has been trained by CNN using random images taken from the database of ImageNet and can work on images taken from a wide range of sources. By saving space on an image by removing redundant areas, the quantity of hidden data can be raised (improve capacity). Since the weights and model architecture are randomized, the actual method in which the network will hide the data can't be known to anyone who does not have the weights. Furthermore, additional block-shuffling is incorporated as an encryption method to improved security; also, the image enhancement methods are used to improving the output quality. From results, the proposed method has achieved high-security level, high embedding capacity. In addition, the result approves that the system achieves good results in visibility and attacks, in which the proposed method successfully tricks observer and the steganalysis program.

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Forecasting the financial failure of Islamic banks using the Altman model, ---- springate model and ---- Sherrod model / an analytical study in Islamic banks listed on the Iraq Stock Exchange
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Profit is a goal sought by all banks because it brings them income and guarantees them survival and continuity, and on the other hand, facing commitments without financial crisis. Hence the idea of research in his quest to build scientific tools and means that can help bank management in particular, investors, lenders and others to predict financial failure and to detect early financial failures. The research has produced a number of conclusions, the most important of which is that all Islamic banks sample a safe case of financial failure under the Altman model, while according to the Springate model all Islamic banks sample a search for a financial failure except the Islamic Bank of Noor Iraq for Investment and Finance )BINI(. A

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Balancing the Multi Assembly line Using Ranked Positional Weight and COMSOAL Algorithms: Case Study at the Sewing line Factory (7) /the General Company for Leather Industries (GCLI/ Baghdad)
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      The problem of multi assembly line balancing appears as one of the most prominent and complex type of problem. The research problem of this dissertation is concerned with choosing the suitable method that includes the nature of the processes of the multi assembly type of the sewing line at factory no. (7). The State Company for Leather Manufacturing. The sewing line currently suffers from idle times at work stations which resulted in low production levels that do not meet the production plans. The authors have devised a flexible simulation model which uses the uniform distribution to generate task time for each shoe type produced by the factory. The simulation of the multi assembly line was based on assigni

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Publication Date
Tue Jan 06 2004
Journal Name
Iraqi Journal Of Science
Cluster and factor analyses R and Q mode technique of geochemical and petrological data of the Shalair Metamorphic Rock Group, Shalair Valley area, Northeastern Iraq
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Publication Date
Thu Oct 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Pressure Control of Electro-Hydraulic Servovalve and Transmission Line Effect
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The effected of the long transmission line (TL) between the actuator and the hydraulic control valve sometimes essentials. The study is concerned with modeling the TL which carries the oil from the electro-hydraulic servovalve to the actuator. The pressure value inside the TL has been controlled by the electro-hydraulic servovalve as a voltage supplied to the servovalve amplifier. The flow rate through the TL has been simulated by using the lumped π element electrical analogy method for laminar flow. The control voltage supplied to servovalve can be achieved by the direct using of the voltage function generator or indirect C++ program connected to the DAP-view program built in the DAP-card data acqu

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Publication Date
Sun Dec 01 2024
Journal Name
Journal Of Economics And Administrative Sciences
Nadaraya-Watson Estimation of a Circular Regression Model on Peak Systolic Blood Pressure Data
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Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Erro

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Preliminary quality assurance of printgrammetry technique-3D modeling from Google Earth 3D imagery data
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Publication Date
Fri Jan 01 2016
Journal Name
Statistics And Its Interface
Search for risk haplotype segments with GWAS data by use of finite mixture models
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The region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Petroleum Science And Engineering
Performance evaluation of analytical methods in linear flow data for hydraulically-fractured gas wells
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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Determination of Optimal Time-Average Wind Speed Data in the Southern Part of Malaysia
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Mersing is one of the places that have the potential for wind power development in Malaysia. Researchers often suggest it as an ideal place for generating electricity from wind power. However, before a location is chosen, several factors need to be considered. By analyzing the location ahead of time, resource waste can be avoided and maximum profitability to various parties can be realized. For this study, the focus is to identify the distribution of the wind speed of Mersing and to determine the optimal average of wind speed. This study is critical because the wind speed data for any region has its distribution. It changes daily and by season. Moreover, no determination has been made regarding selecting the average wind speed used for w

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