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

The systems cooling hybrid solar uses solar collector to convert solar energy into the source of heat for roasting Refrigerant outside of the compressor and this process helps in the transformation of Refrigerant from the gas to a liquid state in two-thirds the top of the condenser instead of two-thirds the bottom of the condenser as in Conventional cooling systems and this in turn reduces the energy necessary to lead the process of cooling. The system cooling hybrid use with a capacity of 1 ton and Refrigerant type R22 and the value of current drawn by the system limits (3.9-4.2A), the same value of electric current calculated by the system are  Conventional  within this atmosphere of Iraq, and after taking different readings

            The research is dealing with the absorption and fluorescence spectra for the hybrid of  an Epoxy Resin doped with organic dye Rhodamine (R6G) of different concentrations (5*10^-6, 5*10^-5, 1*10^-5, 1*10^-4, 5*10^-4) Mol/ℓ at room temperature. The Quantum efficiency Q_fm, the rate of fluorescence emission K_fm (s^-1), the non-radiative lifetime τ_fm (s), fluorescence lifetime τ_f and the Stokes shift were calculated. Also the energy gap (Eg) for each dye concentration was evaluated. The results showed that the maximum quantum effi

The rheological behavior among factors that are present in Stokes law can be used to control the stability of the colloidal dispersion system. The felodipine lipid polymer hybrid nanocarriers  (LPHNs) is an interesting colloidal dispersion system that is used for rheological characteristic analysis. The LPHNs compose of polymeric components and lipids. This research aims to prepare oral felodipine LPHNs to investigate the effect of independent variables on the rheological behavior of the nanosystem. The microwave-based technique was used to prepare felodipine LPHNs (H1-H9) successfully. All the formulations enter the characterization process for particle size and PDI to ascertain the colloidal properties of the prepared nanosystem t

In the present study a new synthesis method has been introduced for the decoration of platinum(Pt) on the functionalized graphene nanoplatelet (GNP) and also highlighted the preparation method of nanofluids. GNP–Pt uniform nanocomposite was produced from a simple chemical reaction procedure, which included acid treatment for functionalization of GNP. The surface characterization was performed by various techniques such as XRD, FESEMand TEM. The effective thermal conductivity, density, viscosity, specific heat capacity and stability of functionalized GNP–Pt water based nanofluids were investigated in different instruments. The GNP–Pt hybrid nanofluids were prepared by dispersing the nanocomposite in base fluid without adding any surfac

The spectral response of the Si solar cell does not coincidence with the sun irradiance spectrum, so the efficiency of the Si solar cell is not high. To improve the Si solar cell one try to make use of most region of the sun spectrum by using dyes which absorb un useful wavelengths and radiate at useful region of spectrum (by stock shift). Fluorescence's dye is used as luminescent concentrator to increase the efficiency of the solar cell. The results show that the performance efficiency and out power for crystalline silicon solar cells are improved.

In this paper, two new simple, fast and efficient block matching algorithms are introduced, both methods begins blocks matching process from the image center block and moves across the blocks toward image boundaries. With each block, its motion vector is initialized using linear prediction that depending on the motion vectors of its neighbor blocks that are already scanned and their motion vectors are assessed. Also, a hybrid mechanism is introduced, it depends on mixing the proposed two predictive mechanisms with Exhaustive Search (ES) mechanism in order to gain matching accuracy near or similar to ES but with Search Time ST less than 80% of the ES. Also, it offers more control capability to reduce the search errors. The experimental tests

Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a