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Deep Learning and Machine Learning via a Genetic Algorithm to Classify Breast Cancer DNA Data
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       This paper uses Artificial Intelligence (AI) based algorithm analysis to classify breast cancer Deoxyribonucleic (DNA). Main idea is to focus on application of machine and deep learning techniques. Furthermore, a genetic algorithm is used to diagnose gene expression to reduce the number of misclassified cancers. After patients' genetic data are entered, processing operations that require filling the missing values using different techniques are used. The best data for the classification process are chosen by combining each technique using the genetic algorithm and comparing them  in terms of accuracy.

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Publication Date
Mon Feb 24 2025
Journal Name
Misan Journal Of Academic Studies
Some of Parametric and Non Parametric Estimations for Circular Regression Model via Simulation
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Circular data (circular sightings) are periodic data and are measured on the unit's circle by radian or grades. They are fundamentally different from those linear data compatible with the mathematical representation of the usual linear regression model due to their cyclical nature. Circular data originate in a wide variety of fields of scientific, medical, economic and social life. One of the most important statistical methods that represents this data, and there are several methods of estimating angular regression, including teachers and non-educationalists, so the letter included the use of three models of angular regression, two of which are teaching models and one of which is a model of educators. ) (DM) (MLE) and circular shrinkage mod

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Science
Periodic Solutions of the Forest Pest System Via Hopf Bifurcation and Averaging Theory
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    This work aims to analyse the dynamic behaviours of the forest pest system. We confirm the forest pest system in plane for limit cycles bifurcating existence from a Hopf bifurcation under certain conditions by using the first Lyapunov coefficient and the second-order of averaging theory. It is shown that all stationary points in this system have Hopf bifurcation points and provide an estimation of the bifurcating limit cycles.

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Publication Date
Sat Jun 03 2023
Journal Name
Iraqi Journal Of Science
Fast encoding algorithm based on Weber's law and Triangular Inequality Theorem
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In the present work, an image compression method have been modified by combining The Absolute Moment Block Truncation Coding algorithm (AMBTC) with a VQ-based image coding. At the beginning, the AMBTC algorithm based on Weber's law condition have been used to distinguish low and high detail blocks in the original image. The coder will transmit only mean of low detailed block (i.e. uniform blocks like background) on the channel instate of transmit the two reconstruction mean values and bit map for this block. While the high detail block is coded by the proposed fast encoding algorithm for vector quantized method based on the Triangular Inequality Theorem (TIE), then the coder will transmit the two reconstruction mean values (i.e. H&L)

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Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Image encryption algorithm based on the density and 6D logistic map
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One of the most difficult issues in the history of communication technology is the transmission of secure images. On the internet, photos are used and shared by millions of individuals for both private and business reasons. Utilizing encryption methods to change the original image into an unintelligible or scrambled version is one way to achieve safe image transfer over the network. Cryptographic approaches based on chaotic logistic theory provide several new and promising options for developing secure Image encryption methods. The main aim of this paper is to build a secure system for encrypting gray and color images. The proposed system consists of two stages, the first stage is the encryption process, in which the keys are genera

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Speech Enhancement Algorithm Based on Super-Gaussian Modeling and Orthogonal Polynomials
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Publication Date
Tue Jun 01 2021
Journal Name
Al-nahrain Journal Of Science
Medical Image Denoising Via Matrix Norm Minimization Problems
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This paper presents the matrix completion problem for image denoising. Three problems based on matrix norm are performing: Spectral norm minimization problem (SNP), Nuclear norm minimization problem (NNP), and Weighted nuclear norm minimization problem (WNNP). In general, images representing by a matrix this matrix contains the information of the image, some information is irrelevant or unfavorable, so to overcome this unwanted information in the image matrix, information completion is used to comperes the matrix and remove this unwanted information. The unwanted information is handled by defining {0,1}-operator under some threshold. Applying this operator on a given ma

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
Hydrogen Production by Water Electrolysis Via Photovoltaic Panel
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Hydrogen fuel is a good alternative to fossil fuels. It can be produced using a clean energy without contaminated emissions. This work is concerned with experimental study on hydrogen production via solar energy. Photovoltaic module is used to convert solar radiation to electrical energy. The electrical energy  is used for electrolysis of water into hydrogen and oxygen by using alkaline water electrolyzer with stainless steel electrodes. A MATLAB computer program is developed to solve a four-parameter-model and predict the characteristics of PV module under Baghdad climate conditions. The hydrogen production system is tested at different NaOH mass concentration of (50,100, 200, 300) gram. The maximum hydrogen produc

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Publication Date
Sat Jan 01 2022
Journal Name
Proceeding Of The 1st International Conference On Advanced Research In Pure And Applied Science (icarpas2021): Third Annual Conference Of Al-muthanna University/college Of Science
Analyze water scarcity in Basrah city via geoinformatics
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A water crisis is a circumstance in which a region accessible potable, unpolluted water is less than the requirement of that country. Two converging trends cause water scarcity, that are expanded use of irrigation, and loss of available freshwater supplies. Water scarcity can arise from two mechanisms, the physical water scarcity because of deficient natural water supply to fulfil the country demand, and economic water scarcity due to bad management for sufficient available water resources. This research examines data set as multispectral Landsat 8 satellite images that are detected for Basrah city, located in southern Iraq, and positioned between Kuwait and Iran on the Shatt al-Arab. Such raw data are satellite images. Using ENVI 5.3 softw

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Publication Date
Sun Jan 01 2023
Journal Name
Proceedings Of International Conference On Data Science And Applications
Very Low Illumination Image Enhancement via Lightness Mapping
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Publication Date
Tue Aug 01 2017
Journal Name
International Journal Of Greenhouse Gas Control
CO2 geo-storage capacity enhancement via nanofluid priming
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CO2 geo-storage efficiency is strongly influenced by the wettability of the CO2-brine-mineral system. With decreasing water-wetness, both, structural and residual trapping capacities are substantially reduced. This constitutes a serious limitation for CO2 storage particularly in oil-wet formations (which are CO2-wet). To overcome this, we treated CO2-wet calcite surfaces with nanofluids (nanoparticles dispersed in base fluid) and found that the systems turned strongly water-wet state, indicating a significant wettability alteration and thus a drastic improvement in storage potential. We thus conclude that CO2 storage capacity can be significantly enhanced by nanofluid priming.