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Offline Signature Verification Based on Neural Network
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The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group of signatures, numbering 70 images, were used. Image preprocessing steps were performed on them, and their features were extracted using the median filter. After that, the eigenvector and eigenvalue were calculated using the PCA algorithm. Then the backpropagation neural network algorithm was applied for training and testing where the performance reached 6.7995e−07 for 82 epochs and the accuracy was 99.98%.

Publication Date
Wed Mar 02 2022
Journal Name
Journal Of Educational And Psychological Researches
King Khalid University towards Strategies Compatible with Brain-Based Learning (BBL)
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The study aimed to reveal the level of knowledge and tendencies of high- study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with brain-based learning (BBL). And Then, putting a proposed concept to develop knowledge and tendencies of high-study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with Brain-based learning (BBL). For achieving this goal, a cognitive test and a scale of tendency were prepared to apply harmonious strategies with brain-based learning. The descriptive approach was used because it suits the goals of the study. The study sample consisted of (70) male and female students of postgraduate

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Publication Date
Sat Jan 10 2015
Journal Name
British Journal Of Mathematics & Computer Science
The Use of Gradient Based Features for Woven Fabric Images Classification
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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
Iraqi Bauxite and Porcalinite Rocks Based Refractory, Preparation and Studying Properties
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Abstract 

Locally natural occurring Iraqi rocks of Bauxite and Porcelanite (after pre calcinations at 1000oC for 1hr) were used, with the addition of different proportions of MgO and Al2O3, to prepare refractory materials. The effects of these additives on the physical and thermal properties of the prepared refractories were investigated.

Many batches of Bauxite/MgO, Bauxite/Al2O3, Bauxite/MgO/Al2O3, and   Porcelanite/ MgO/Al2O3 were prepared. The mixture is milled and classified into different size fractions; fine (less than 45μm) 40%, middle (45-75μm) 40%, and coarse (75-106μm) 20% .

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Multiwavelet and Estimation by Interpolation Analysis Based Hybrid Color Image Compression
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Nowadays, still images are used everywhere in the digital world. The shortages of storage capacity and transmission bandwidth make efficient compression solutions essential. A revolutionary mathematics tool, wavelet transform, has already shown its power in image processing. The major topic of this paper, is improve the compresses of still images by Multiwavelet based on estimation the high Multiwavelet coefficients in high frequencies sub band  by interpolation instead of sending all Multiwavelet coefficients. When comparing the proposed approach with other compression methods Good result obtained

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Severity Based Light-Weight Encryption Model for Secure Medical Information System
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Thu Apr 29 2021
Journal Name
Iraqi Journal Of Science
Capacitance and Resistivity Measurements of Polythiophene /Metallic Nanoparticles-based Humidity Sensors
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Capacitive–resistive humidity sensors based on polythiophene (P3HT) organic semiconductor as an active material hybrid with three types of metallic nanoparticles (NP) (Ag, Al, and Cu) were synthesized by pulsed laser ablation (PLA). The hybrid P3HT/metallic nanoparticles were deposited on indium-tin-oxide (ITO) substrate at room temperature. The surface morphology of theses samples was studied by using field emission scanning electron micrographs (FE-SEM), which indicated the formation of nanoparticles with grain size of about 50nm. The electrical characteristics of the sensors were examined as a function of the relative humidity levels. The sensors showed an increase in the capacitance with variation in the humidity level.  Whil

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Publication Date
Sat Mar 01 2014
Journal Name
Renewable Energy
Field study of various air based photovoltaic/thermal hybrid solar collectors
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In the present work a comparative study for thermal and electrical performance of different hybrid photovoltaic/thermal collectors designs for Iraq climate conditions have been carried out. Four different types of air based hybrid PV/T collectors have been manufactured and tested. Three collectors consist of four main parts namely, channel duct, glass cover, axial fan to circulate air and two PV panels in parallel connection. The measured parameters are, the temperature of the upper and the lower surfaces of the PV panels, air temperature along the collector, air flow rate, pressure drop, power produced by solar cell, and climate conditions such as wind speed, solar radiation and ambient temperature. The thermal and hydraulic performances o

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
An Electronic and Web-Based Authentication, Identification, and Logging Management System
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The need for participants’ performance assessments in academia and industry has been a growing concern. It has attendance, among other metrics, is a key factor in engendering a holistic approach to decision-making. For institutions or organizations where managing people is an important yet challenging task, attendance tracking and management could be employed to improve this seemingly time-consuming process while keeping an accurate attendance record. The manual/quasi-analog approach of taking attendance in some institutions could be unreliable and inefficient, leading to inaccurate computation of attendance rates and data loss. This work, therefore, proposes a system that employs embedded technology and a biometric/ w

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Publication Date
Sat Apr 30 2016
Journal Name
Environmental Science And Pollution Research
Risk-based prioritization of pharmaceuticals in the natural environment in Iraq
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