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.
Globally, the COVID-19 pandemic’s development has presented significant societal and economic challenges. The carriers of COVID-19 transmission have also been identified as asymptomatic infected people. Yet, most epidemic models do not consider their impact when accounting for the disease’s indirect transmission. This study suggested and investigated a mathematical model replicating the spread of coronavirus disease among asymptomatic infected people. A study was conducted on every aspect of the system’s solution. The equilibrium points and the basic reproduction number were computed. The endemic equilibrium point and the disease-free equilibrium point had both undergone local stability analyses. A geometric technique was used
... Show MoreThe species Spongilla lacustris was identified for the first time in Iraq, it was found during winter 1998 in an irrigation canal within the campus of the University of Baghdad (Jadiriah), water is drawn from Tigris river. The specimens were found in water samples of sizes ranging between 5-50 cm with yellowish color . It was found in two habitats , one as attached on submerged aquatic plant Ceratophyllum sp., and the other on the canal bottom (concret material). Some physico- chemical characters were determined including conductivity ,salinity , pH, total alkalinity, total hardness, Ca ,Mg ,anddissolved oxygen. Water quality was fresh , alkaline, hard and well aerated.
In this research four steps of the new derivatives of Naproxen drug have been made which are known as a high medicinal effectiveness; the first step involved converting Naproxen into the corresponding ester (A) by reaction Naproxen with methanol absolute in presence H2SO4. While the second step involved treatment methyl Naproxen ester (A) with hydrazine hydrate 80% in presence of ethanol .The third reaction requires synthesis of Schiff bases (C1-C10) by condensation. of Naproxen hydrazide (B) with many substituted aromatic aldehydes . Finally, the fourth step synthesized new tetrazole derivatives ( D1- D10) by the reaction of the prepared Schiff bases (in the third step) with Sodium azide in THF as a solvent .The prepared compounds wer
... Show MoreA series of new 2-quinolone derivatives linked to benzene sulphonyl moieties were performed by many steps: the first step involved preparation of different coumarins (A1,A2) by condensation of different substituted phenols with ethyl acetoacetate. The compound A1 was treated with nitric acid to afford two isomers of nitrocoumarin derivatives (A3) and (A4). The prepared compounds (A2, A3) were treated with hydrazine hydrate to synthesize different 2-quinolone compounds (A5,A6) while the coumarin treated with different amines gave compounds (A7,A8). Then the synthesized 2-quinolone compounds (A5-A8) treated with benzene sulphonyl chloride to afford new sulfonamide derivatives (A9-A12). The synthesized compounds were characterized by FT-IR, 1H
... Show MoreIn this work, N-hydroxy phthalimide derivatives (NHPID) were synthesized from the nucleuphilic substitution reactions of (NHPI) with different halides (alkyl halides, sulfonyl halides, benzoyl halides and benzyl halides). The products were distinguished using FTIR spectrum and Nuclear magnetic resonsnce (1H-NMR and 13CNMR), in addition to other characteristic methods such as sodium fution for sulfur determination. followed by measuring antibacterial (with different types of gram positive/gram negative bacteria) and antifungal activities of these compounds.
In-vitro biological activities of the free new H4L ( indole-7-thiocarbohydrazone) ligand and its Ni(II), Pd(II) , Pt(II), Cu(II), Ag(I), Zn(II) and Cd(II) complexes are screened against two cancerous cell lines, that revealed significant activity only for [Cu2Cl2(H4L)2(PPh3)2] after 72 h treatment by the highest tested concentrations. The Copper(I) complex was characterized by X-ray Crystallography and the NMR spectra, whereas it has been confirmed to have momentous cytotoxicity against ovarian, breast cancerous cell lines (Caov-3, MCF-7). The apoptosis-inducing properties of the Cu(I) complex have been investigated through fluorescence microscopy visualization, DNA fragmentation analysis and propidium iodide flow cytometry.