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Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep learning model was utilized to resize images and feature extraction. Finally, different ML classifiers have been tested for recognition based on the extracted features. The effectiveness of each classifier was assessed using various performance metrics. The results show that the proposed system works well, and all the methods achieved good results; however, the best results obtained were for the Support Vector Machine (SVM) with a linear kernel.

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Tue Jan 08 2019
Journal Name
Lubricants
Influence of Sample Mixing Techniques on Engine Oil Contamination Analysis by Infrared Spectroscopy
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For the most reliable and reproducible results for calibration or general testing purposes of two immiscible liquids, such as water in engine oil, good emulsification is vital. This study explores the impact of emulsion quality on the Fourier transform infrared (FT-IR) spectroscopy calibration standards for measuring water contamination in used or in-service engine oil, in an attempt to strengthen the specific guidelines of ASTM International standards for sample preparation. By using different emulsification techniques and readily available laboratory equipment, this work is an attempt to establish the ideal sample preparation technique for reliability, repeatability, and reproducibility for FT-IR analysis while still considering t

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Science
A Study of Desertification Using Remote Sensing Techniques in Basra Governorate, South Iraq
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Iraq territory as a whole and south of Iraq in particular encountered rapid desertification and signs of severe land degradation in the last decades. Both natural and anthropogenic factors are responsible for the extent of desertification. Remote sensing data and image analysis tools were employed to identify, detect, and monitor desertification in Basra governorate. Different remote sensing indicators and image indices were applied in order to better identify the desertification development in the study area, including the Normalized difference vegetation index (NDVI), Normalized Difference Water Index (NDWI), Salinity index (SI), Top Soil Grain Size Index (GSI) , Land Surface Temperature (LST) , Land Surface Soil Moisture (LSM), and La

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Publication Date
Sat Dec 01 2012
Journal Name
2012 International Conference On Radar, Communication And Computing (icrcc)
BER performance improvement for secure wireless communication systems based on CSK- STBC techniques
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There has been a growing interest in the use of chaotic techniques for enabling secure communication in recent years. This need has been motivated by the emergence of a number of wireless services which require the channel to provide very low bit error rates (BER) along with information security. This paper investigates the feasibility of using chaotic communications over Multiple-Input Multiple-Output (MIMO) channels by combining chaos modulation with a suitable Space Time Block Code (STBC). It is well known that the use of Chaotic Modulation techniques can enhance communication security. However, the performance of systems using Chaos modulation has been observed to be inferior in BER performance as compared to conventional communication

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Publication Date
Sat Dec 30 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Charge Transfer Between d-p States in Ti02 By Employing Compton Scattering Techniques
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The com pton profiles for Ti02 have been measured using a SCi

Am-241 compton spectrometer .A pellet of the oxide was prepared from a polycrystalline powder    having a thickness of 1.54 mm ,about J 00000  counts   have   been  accumulated   at   the  compton   peak

.Theoreti cal compton profiles have been calculated for different ionic anangements using free atom compton profile for the core electrons.The   theoretical  and  experimental  results  ahrce  well  for (Ti/4(0 .2    arrangement which support complete transfer of valence electrons from metal to oxygen ions, i.e., full ionic &nbs

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Publication Date
Tue Aug 15 2023
Journal Name
Journal Of Economics And Administrative Sciences
Machine Learning Techniques for Analyzing Survival Data of Breast Cancer Patients in Baghdad
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The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An exploratory study of history-based test case prioritization techniques on different datasets
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In regression testing, Test case prioritization (TCP) is a technique to arrange all the available test cases. TCP techniques can improve fault detection performance which is measured by the average percentage of fault detection (APFD). History-based TCP is one of the TCP techniques that consider the history of past data to prioritize test cases. The issue of equal priority allocation to test cases is a common problem for most TCP techniques. However, this problem has not been explored in history-based TCP techniques. To solve this problem in regression testing, most of the researchers resort to random sorting of test cases. This study aims to investigate equal priority in history-based TCP techniques. The first objective is to implement

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Slip Effect on the Peristaltic Transport of MHD Fluid through a Porous Medium with Variable Viscosity
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The present paper concerns with peristaltic analysis of MHD viscous fluid in a two dimensional channel with variable viscosity through a porous medium under the effect of slip condition. Along wave length and low Reynolds number assumption is used in the problem formulation. An analytic solution is presented for the case of hydrodynamic fluid while for magneto hydrodynamic fluid a series solution is obtained in the small power of viscosity parameter. The salient features of pumping and trapping phenomena are discussed in detail through a numerical integration. The features of the flow characteristics are analyzed by plotting graphs and discussed in detail. When .

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Computational Study of the Flow of Newtonian Fluid Through A Straight Channel and Lid-Driven Cavity
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     This article aims to introducenumerical study of two different incompressible Newtonian fluid flows. The first type of flow is through the straight channel, while the second flow is enclosed within a square cavity and the fluid is moved by the upper plate at a specific velocity. Numerically, a Taylor-Galerkin\ pressure-correction finite element method (TGPCFEM) is chosen to address the relevant governing equations. The Naiver-Stoke partial differential equations are usually used to describe the activity of fluids. These equations consist of the continuity equation (conservation of mass) and the time-dependent conservation of momentum, which are preserved in Cartesian coordinates. In this study, the effect of Reynolds number (

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