Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven classifiers. A hybrid supervised learning system that takes advantage of rich intermediate features extracted from deep learning compared to traditional feature extraction to boost classification accuracy and parameters is suggested. They provide the same set of characteristics to discover and verify which classifier yields the best classification with our new proposed approach of “hybrid learning.” To achieve this, the performance of classifiers was assessed depending on a genuine dataset that was taken by our camera system. The simulation results show that the support vector machine (SVM) has a mean square error of 0.011, a total accuracy ratio of 98.80%, and an F1 score of 0.99. Moreover, the results show that the LR classifier has a mean square error of 0.035 and a total ratio of 96.42%, and an F1 score of 0.96 comes in the second place. The ANN classifier has a mean square error of 0.047 and a total ratio of 95.23%, and an F1 score of 0.94 comes in the third place. Furthermore, RF, WKNN, DT, and NB with a mean square error and an F1 score advance to the next stage with accuracy ratios of 91.66%, 90.47%, 79.76%, and 75%, respectively. As a result, the main contribution is the enhancement of the classification performance parameters with images of varying brightness and clarity using the proposed hybrid learning approach.
AlPO4 catalysts supported with WO3 were prepared by impregnating the catalysts with ammonium metatungstate. The catalysts were checked by X-ray Diffraction (XRD), AFM, and SEM; also, the catalysts analysis was done by X-Ray (EDX). Finally, the N2 adsorption-desorption was used to measure the pore volume and surface area of the catalyst. The prepared catalyst has a surface area of 185.83 m2/g, pore volume of 0.645 cm3/g at a calcination temperature of 500°C for 3 hrs, and particle size of AlPO4 with an average of 35.36 nm. Transesterification of edible oil using WO3/AlPO4 was performed, it was observed that WO3/AlPO4 catalysts give high conversion of edible oil, and this is attributed to the high surface area, smaller particle size, and the
... Show MoreObjective: To study the effect of epidural spinal injection over one year in case of spinal stenosis. Methodology: This prospective study included 566 patients with spinal stenosis seen at Al-Kindy Teaching and Al-Sader, Hospitals who were treated by local epidural steroid injection. They were followed up for at least five subsequent visits after seven days, one month, three months, six months, and one year to assess efficacy. Result: Mean age of patients was 49.5 years, with a predominance of females (65%). L4/L5 was the most involved level in the spinal stenosis (70%). Grade II stenosis accounted for (45.4%) of cases. The pairwise comparison revealed that there was significant decrease in proportions of patients with pain in day
... Show MoreToxic substances have been released into water supplies in recent decades because of fast industrialization and population growth. Fenton electrochemical process has been addressed to treat wastewater which is very popular because of its high efficiency and straightforward design. One of the advanced oxidation processes (AOPs) is electro-Fenton (EF) process, and electrode material significantly affects its performance. Nickel foam was chosen as the source of electro-generated hydrogen peroxide (H2O2) due to its good characteristics. In the present study, the main goals were to explore the effects of operation parameters (FeSO4 concentration, current density, and electrolysis time) on the catalytic perform
... Show MoreThis paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF
... Show MoreIn this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo
... Show MoreA simple and accurate method to determinate furosemide (FUR) based on converting the secondary amine to primary amine with acidic hydrolysis then azotization by nitrous acid and coupled with resorcinol as a coupling agent in aqueous medium at pH 13. The optical characteristic like beers law limit found to be (0.25-2.5) μg.ml−1, detection and quantification limits (0.0196) (0.0654) μg.ml−1respectivly and Sandel sensitivity was 0.006738 μg.cm−2. The least-square method was used to evaluate the regression equation and the correlation coefficient. The resulted azo dye has a maximum absorbance at 430 nm with light oran
The aerodynamic characteristics of the forward swept wing aircraft have been studied theoretically and experimentally. Low order panel method with the Dirichlet boundary condition have been used to solve the case of the steady, inviscid and compressible flow. Experimentally, a model was manufactured from wood to carry out the tests. The primary objective of the experimental work was the measurements of the wake dimensions and orientation, velocity defect along the wake and the wake thickness. A blower type low speed (open jet) wind tunnel was used in the experimental work. The mean velocity at the test section was (9.3 m/s) and the Reynolds number based on the mean aerodynamic chord and the mean velocity was (0.46x105). The measurements sho
... Show MoreThe performa of evaluation process is a process that should be carried out by all industrial management in order to stand on aspects of development or underdevelopment of the various departments and activities in its industrial project for the purpose of identifying obstacles and find out the causes and then avoid them quickly. And intended to rectify the performance evaluation of the activities of industrial project or economic union by measuring the results achieved within a specific operational process and compare it to what is already targeted, and often the time for comparison of one year.
The process of performance evaluation depends upon several criteria and indicators within the
... Show MoreThis work presents the construction of a test apparatus for air-conditioning application that is flexible in changing a scaled down adsorbent bed modules. To improve the heat and mass transfer performance of the adsorbent bed, a finned-tube of the adsorbent bed heat exchanger was used. The results show that the specific cooling power (SCP) and the coefficient of performance (COP) are 163 W/kg and 0.16, respectively, when the cycle time is 40 min, the hot water temperature is 90oC, the cooling water temperature is 30oC and the evaporative water temperature is 11.4oC.
The energy requirements of corn silage harvesters and the application of precision agricultural techniques are essential for efficient and productive agricultural practices. The article aims to review previous studies on the energy requirements needed for different corn silage harvesting machines, and on the other hand, to present methods for measuring corn silage productivity directly in the field and monitoring it based on microcontrollers and artificial intelligence techniques. The process of making corn silage is done by cutting green fodder plants into small pieces, so special harvesters are used for this, called corn silage harvesters. The purpose of harvesting corn silage is to efficiently collect and store as many digestible nutrien
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