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Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer learning, a powerful deep learning technique that can be effectively employed to Face gender classification using the Alex-Net architecture. The performance evaluation of the proposed gender classification model encompassed three datasets: the LFW dataset, which contained 1,200 facial images. The Faces94 dataset contained 400 facial images, and the family dataset had 400. The Transfer Learning with the Alex-Net model achieved an accuracy of 98.77% on the LFW dataset.

Furthermore, the model attained an accuracy rate of 100% on both the Faces94 and family datasets. Thus, the proposed system emphasizes the significance of employing pre-processing techniques and transfer learning with the Alex-Net model. These methods contribute to more accurate results in gender classification. Where, the results achieved by applying image contrast enhancement techniques, such as HE and CLAHE, were compared. CLAHE achieved the best facial classification accuracy compared to HE.

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Publication Date
Sat Jan 01 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

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Publication Date
Sun Nov 19 2023
Journal Name
Aip Conference Proceedings
Designing a database for a three dimensional model using geomatics techniques
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Publication Date
Mon Oct 22 2018
Journal Name
Journal Of Economics And Administrative Sciences
Using simulation to compare between parametric and nonparametric transfer function model
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In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t

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Publication Date
Sun Jan 01 2023
Journal Name
International Conference Of Computational Methods In Sciences And Engineering Iccmse 2021
Penetration of charged particles in ZnO using energy loss function model
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In this paper, we propose an approach to estimate the induced potential, which is generated by swift heavy ions traversing a ZnO thin film, via an energy loss function (ELF). This induced potential is related to the projectile charge density, ρq(k) and is described by the extended Drude dielectric function. At zero momentum transfer, the resulting ELF exhibits good agreement with the previously reported results. The ELF, obtained by the extended Drude model, displays a realistic behavior over the Bethe ridge. It is observed that the induced potential relies on the heavy ion velocity and charge state q. Further, the numerical results show that the induced potential for neutral H, as projectile, dominates when the heavy ion velocity is less

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Publication Date
Thu Jun 17 2021
Journal Name
Revista Iberoamericana De PsicologÍa Del Ejercicio Y El Deporte
THE EFFECT OF USING THE ELECTRONIC PARTICIPATORY LEARNING STRATEGY ACCORDING TO THE WEB PROGRAMS IN LEARNING SOME BASIC SKILLS OF BASKETBALL FOR FIRST-GRADE INTERMEDIATE SCHOOL STUDENTS ACCORDING TO THE CURRICULAR COURSE
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The research aims to identify the impact of using the electronic participatory learning strategy according to internet programs in learning some basic basketball skills for middle first graders according to the curricular course, and the sample of research was selected in the deliberate way of students The first stage of intermediate school.As for the problem of research, the researchers said that there is a weakness in the levels of school students in terms of teaching basketball skills, which prompted the researchers to create appropriate solutions by using a participatory learning strategy.The researchers imposed statistically significant differences between pre and post-test tests, in favor of the post tests individually and in favor of

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Publication Date
Tue Jan 01 2013
Journal Name
Thesis
User Authentication Based on Keystroke Dynamics Using Artificial Neural Networks
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Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

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Publication Date
Tue Feb 01 2022
Journal Name
Svu-international Journal Of Engineering Sciences And Applications
Water Quality Detection using cost-effective sensors based on IoT
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Publication Date
Thu Nov 25 2021
Journal Name
Engineering And Technology Journal
Pentacene Based Organic Field Effect Transistor Using Different Gate Dielectric
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This paper presents the electrical behavior of the top contact/ bottom gate of an organic field-effect transistor (OFET) utilizing Pentacene as a semiconductor layer with two distinctive gate dielectric materials Polyvinylpyrrolidone (PVP) and Zirconium oxide (ZrO2) were chosen. The influence of the monolayer and bilayer gates insulator on OFET performance was investigated. MATLAB software was used to simulate and determine the electrical characteristics of a device. The output and transfer characteristics were studied for ZrO2, PVP and ZrO2/PVP as an organic gate insulator layer. Both characteristics show a high drain current at the gate dielectric ZrO2/PVP equal to -0.0031A and -0.0015A for output and transfer characteristics respectively

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Enhancement Ear-based Biometric System Using a Modified AdaBoost Method
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          The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Image Steganography using Dynamic Threshold based on Discrete Cosine Transform
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The art of preventing the detection of hidden information messages is the way that steganography work. Several algorithms have been proposed for steganographic techniques. A major portion of these algorithms is specified for image steganography because the image has a high level of redundancy. This paper proposed an image steganography technique using a dynamic threshold produced by the discrete cosine coefficient. After dividing the green and blue channel of the cover image into 1*3-pixel blocks, check if any bits of green channel block less or equal to threshold then start to store the secret bits in blue channel block, and to increase the security not all bits in the chosen block used to store the secret bits. Firstly, store in the cente

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