Chaotic features of nuclear energy spectrum in ⁶⁸Ge nucleus are investigated by nuclear shell model. The energies are calculated through doing shell model calculations employing the OXBASH computer code with effective interaction of F5PVH. The ⁶⁸Ge nucleus is supposed to have an inert core of ⁵⁶Ni with 12 nucleons (4 protons and 8 neutrons) move in the f5p-model space ( and ). The nuclear level density of considered classes of states is seen to have a Gaussian form, which is in accord with the prediction of other theoretical studies. The statistical fluctuations of the energy spectrum (the level spacing P(s) and the Dyson-Mehta (or statistics) are well described by the Gaussian orthogonal ens

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

Phase change materials are known to be good in use in latent heat thermal energy storage (LHTES) systems, but one of their drawbacks is the slow melting and solidification processes. So that, in this work, enhancing heat transfer of phase change material is studied experimentally for in charging and discharging processes by the addition of high thermal conductive material such as copper in the form of brushes, which were added in both PCM and air sides. The additions of brushes have been carried out with different void fractions (97%, 94% and 90%) and the effect of four different air velocities was tested. The results indicate that the minimum brush void fraction gave the maximum heat transfer in PCM and reduced the time

Ricinus communis L. is an important medical plant hence it contains many active compounds. The aim of this research is to study the effect of plant growth regulators on callus induction and Rutin concentration. A combination of Benzyle adenine (BA) and Indol Acetic acid (IAA) at (0.0,1.0,2.0) mg/L was added to the media, the highest fresh weight of the induced callus from stem explant was (4.97) gr . at (1.0,1.0) mg/L BA and IAA consenquently the same combination gave the highest dry weight of callus (0.42) gr. while the combination at (2.0,1.0) mg/L BA and IAA gave the highest fresh weight of induced callus from Leaves explant (5.28) gr., then (2.0,1.0) mg/L BA and IAA gave the highest dry weight for callus induced from leaves at (0.55

Blades of gas turbine are usually suffered from high thermal cyclic load which leads to crack initiated and then crack growth and finally failure. The high thermal cyclic load is usually coming from high temperature, high pressure, start-up, shut-down and load change. An experimental and numerical analysis was carried out on the real blade and model of blade to simulate the real condition in gas turbine. The pressure, temperature distribution, stress intensity factor and the thermal stress in model of blade have been investigated numerically using ANSYS V.17 software. The experimental works were carried out using a particular designed and manufactured rig to simulate the real condition that blade suffers from. A new cont