Experimental study has been conducted for laminar natural convection heat transfer of air flow through a rectangular enclosure fitted with vertical partition. The partition was oriented parallel to the two vertical isothermal walls with different temperatures, while all the other surfaces of the enclosure were insulated. In this study a test rig has been designed and constructed to allow studying the effect of Rayleigh number, aperture height ratio, partition thickness, the position of aperture according to the side walls and according to the height, the position of the partition according to the hot wall, and partition inclination. The experiments were carried out with air as the working fluid for Rayleigh number range (5*107 – 1.3*10

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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 class

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 class

This article introduces a numerical study on heat exchange and corrosion coefficients of Zinc–water nanofluid stream in a circular tube fitted with swirl generator utilizing CFD emulation. Different  forms of swirl generator which have the following properties of plain twisted tape (PTT) and baffle wings twisted tape (BTT) embeds with various ratio of twisting (y = 2.93, 3.91 and 4.89), baffle inclination angles (β = 0°, - 30° and 30) joined with 1%, 1.5% and 2% volume fraction of ZnO nanofluid were utilized for simulation. The results demonstrated that the heat and friction coefficients conducted by these two forms of vortex generator raised with Reynolds number, twist ratio and baffle inclination angles decreases. Likewise, t

The present work describes numerical and experimental investigation of the heat transfer characteristics in a plate-fin, having built-in piezoelectric actuator mounted on the base plate (substrate). The geometrical configuration considered in the present work is representative of a single element of the plate-fin and triple fins. Air is taken as the working fluid. A performance data for a single rectangular fin and triple fins are provided for different frequency levels (5, 30 and
50HZ) , different input power (5,10,20,30,40 and 50W) and different inlet velocity (0.5, 1, 2, 3, 4, 5 and 6m/s) for the single rectangular fin and triple fins with and without oscillation. The investigation was also performed with different geometrical fin

This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ