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 system's performance. method, the classification accuracy has been compared using different types of classifiers. These classifiers are Naïve Bayesian, KNN, J48, and SVM. The range of the identification accuracy for all the processed databases using the proposed scenario is between (%93.8- %97.8). The system was executed using MATHLAB R2017, 2.10 GHz processor, and 4 GB RAM.
S a mples of compact magnesia and alumina were evaporated
using CO2-laser .The
Processed powders were characterized by electron microscopy
and both scanning and transmission electron microscope. The results
indicated that the particle size for both powders have reduced largely
to 0.003 nm and 0.07 nm for MgO and Al2O3, with increasing in
shape sphericity.
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,
... Show MoreThe denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing. Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds. This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin
... Show MoreNovel 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.
Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result
... Show MoreThis research aims were to evaluate management of broiler production projects in Baghdad province via using the criteria of management, included production index and economic figure (PI and EF) that specified to those projects. in addition to criteria of economic efficiency also applied (INME) index number of management efficiency, in order to the research requirements, data were obtained based on a questionnaire prepared for this purpose, which was collected by personal interview of (60) projects of the broiler production projects from (516) projects representing 11.6% of the research community in Baghdad province in 2016. The results show that mean of PI and EF was (338). The increase in these two criteria is generally due to co
... Show MoreThe efficiency of management is determining factor for the success or failure of agricultural projects generally and Livestock particularly achieving its objectives. Therefore, this research came to diagnose the most important variables that determine the efficiency of management using the probability regression models to measure the probability of management efficient of broilers production projects using random sample included (60) broilers projects represented 11.6% of Baghdad province (research community) in 2016. After estimating the relationship between the management efficiency (descriptive dependent variable) and the independent variables affecting it (age, educational level, production index (PI), experience). The results
... Show MoreKE Sharquie, AA Noaimi, EA Al-Janabi…, Journal of Cosmetics, Dermatological Sciences and Applications, 2013 - Cited by 13
One-third of the total waste generated in the world is construction and demolition waste. Reducing the life cycle of building materials includes increasing their recycling and reuse by using recycled aggregates. By preventing, the need to open new aggregate quarries and reducing the amount of construction waste dumped into landfills, the use of recycled concrete aggregate in drum compacted concrete protects the environment. Four samples of PRCC were prepared for testing (compressive strength, tensile strength, flexural strength, density, water absorption, porosity) as the reference mix and (10, 15, and 20%) of fine recycled concrete aggregate as a partial replacement for fine natural aggregate by volume. The mix is designed according to
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