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.
Flying Ad hoc Networks (FANETs) has developed as an innovative technology for access places without permanent infrastructure. This emerging form of networking is construct of flying nodes known as unmanned aerial vehicles (UAVs) that fly at a fast rate of speed, causing frequent changes in the network topology and connection failures. As a result, there is no dedicated FANET routing protocol that enables effective communication between these devices. The purpose of this paper is to evaluate the performance of the category of topology-based routing protocols in the FANET. In a surveillance system involving video traffic, four routing protocols with varying routing mechanisms were examined. Additionally, simulation experiments conduct
... Show MoreThe inhibitory behavior of L-Cysteine (Cys) and its derivatives towards iron corrosion through density functional theory (DFT) was investigated. The current research study undertakes a rigorous evaluation of global as well as local reactivity descriptors of the Cys in protonated as well as neutral forms and the changes in reactivity after the combination of Cys into di- and tripeptides. The inhibitory effect of di- and tri-peptides increases since, in the molecular structure, the number of reaction centers increase. We computed the adsorption energies (Eads) and low energy complexes with most stability for the adsorption of small peptides and Cys amino acids onto the surfaces of Fe (1 1 1). We found that the adsorption of tri-peptides onto
... Show MoreComputer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
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This paper analyses the relationship between selected macroeconomic variables and gross domestic product (GDP) in Saudi Arabia for the period 1993-2019. Specifically, it measures the effects of interest rate, oil price, inflation rate, budget deficit and money supply on the GDP of Saudi Arabia. The method employs in this paper is based on a descriptive analysis approach and ARDL model through the Bounds testing approach to cointegration. The results of the research reveal that the budget deficit, oil price and money supply have positive significant effects on GDP, while other variables have no effects on GDP and turned out to be insignificant. The findings suggest that both fiscal and monetary policies should be fo
... Show MoreExisting leachate models over–or underestimates leachate generation by up to three orders of magnitude. Practical experiments show that channeled flow in waste leads to rapid discharge of large leachate volumes and heterogeneous moisture distribution. In order to more accurately predict leachate generation, leachate models must be improved. To predict moisture movement through waste, the two–domain PREFLO, are tested. Experimental waste and leachate flow values are compared with model predictions. When calibrated with experimental parameters, the PREFLO provides estimates of breakthrough time. In the short term, field capacity has to be reduced to 0.12 and effective storage and hydraulic conductivity of the waste must be increased to
... Show MoreA simple, precise, rapid, and accurate reversed – phase high performance liquid chromatographic method has been developed for the determination of guaifenesin in pure from pharmaceutical formulations.andindustrial effluent. Chromatography was carried out on supelco L7 reversed- phase column (25cm × 4.6mm), 5 microns, using a mixture of methanol –acetonitrile-water: (80: 10 :10 v/v/v) as a mobile phase at a flow rate of 1.0 ml.min-1. Detection was performed at 254nm at ambient temperature. The retention time for guaifenesin was found 2.4 minutes. The calibration curve was linear (r= 0.9998) over a concentration range from 0.08 to 0.8mg/ml. Limit of detection (LOD) and limit of quantification ( LOQ) were found 6µg/ml and 18µg/ml res
... Show MoreConditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.
Samarium ions (Sm +3), a rare-earth element, have a significant optical emission within the visible spectrum. PMMA samples, mixed with different ratios of SmCl3.6H2O, were prepared via the casting method. The composite was tested using UV-visible, photoluminescence and thermogravimetric analysis (TGA). The FTIR spectrometry of PMMA samples showed some changes, including variation in band intensity, location, and width. Mixed with samarium decreases the intensity of the CO and CH2 stretching bands and band position. A new band appeared corresponding to ionic bonds between samarium cations with negative branches in the polymer. These variations indicate complex links between the Sm +3 ion and oxygen in the ether group. The optical absorption
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