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.
Experimental investigation of the influence of inserting the metal foam to the solar chimney to induce natural ventilation are described and analyzed in this work. To carry out the experimental test, two identical solar chimneys (without insertion of metal foam and with insertion of metal foam) are designed and placed facing south with dimensions of length× width× air gap (2 m× 1 m× 0.2 m). Four incline angles are tested (20o,30o,45o,60o) for each chimney in Baghdad climate condition (33.3o latitude, 44.4o longitude) on October, November, December 2018. The solar chimney performance is investigated by experimentally recording absorber pl
... Show MoreThe aim of the present study is to examine the effectiveness of a proposed unite in voluntary work in enhancing critical thinking skills and the attitudes towards responsible citizenship among eighth grade female students in the Sultanate of Oman. In order to collect the study data, the researchers employed a quasi-experimental research design with twenty female students from Al-Sideeqah bint Al-Sideeq for basic education school. The research data were collected via a critical thinking test that consisted of twenty-five items and a scale of twenty items under three different dimensions, which aimed to measure students' attitudes towards responsible citizenship. The researchers implemented these two instruments as pre- and post the experi
... Show MoreEnsuring security, integrity, and reliability of the election process consider as the main challenges in the electronic voting system. This paper describes the e-voting system by integrating the biometric authentication, advanced encryption, and watermarking techniques towards meeting such challenges. The system employs the fingerprint authentication by utilizing the Scale-Invariant Feature Transform (SIFT) for verifying the identity of the voter to ensure genuineness and non-repudiation of the service. The vote will be encrypted with the AES-GCM technique to be employed in securing the voting process, thus ensuring both data privacy and integrity. Hybrid Blind Watermarking employs the technique of Discrete Wavelet Transform (DWT) a
... Show MoreThe main object of the current work was to determine the antifungal efficiency of secondary metabolites product called synephrine that extracted from Citrus sinesis peels and the ability of synephrine to biosynthesis gold nanoparticles from HAucl4 which consider environmentally favourable method, then determine their activity against pathogenic human dermatophyte. The identification of synephrine done by Thin layer chromatography (TLC), High Performance Liquid Chromatography (HPLC) and The Fourier Transform Infrared (FTIR). The characterization of gold nanoparticles by using Ultra Violet-Visible Spectroscopy (UV-Vis), Field – Emission Scanning Electron Microscopy (FESEM) and Fourier Transform Infrared (FTIR), confirmed the biosynt
... Show MoreAbstract
The current research aims to identify the effect of the proposed strategy in accordance with realistic mathematics on the achievement and mathematical Interrelation of third Intermediate students. Two samples were tested from the middle third grade in a school affiliated with the General Directorate of Baghdad- Rusafa, the first for the academic year (2022-2021). The experimental group is (30) students taught according to the proposed strategy, and the control group is (30) students based on the traditional method. To achieve the research objective, the researchers developed a test for achievement consisting of (30) items and a test of sports interconnection composed of (20) items. The results of the stu
... Show MoreThe aim of this research is to diagnose the impact of competitive dimensions represented by quality, cost, time, flexibility on the efficiency of e-learning, The research adopted the descriptive analytical method by identifying the impact of these dimensions on the efficiency of e-learning, as well as the use of the statistical method for the purpose of eliciting results. The research concluded that there is an impact of the competitive dimensions on the efficiency of e-learning, as it has been proven that the special models for each of the research hypotheses are statistically significant and at a level of significance of 5%, and that each of these dimensions has a positive impact on the dependent variable, and the research recommended
... Show More