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 issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

Recent studies have proved the important role of fungi in the biodegradation of oil pollutants. The present study aims to find the optimal conditions for the fungi to get the best rate of the biodegradation of the polycyclic aromatic hydrocarbon (PAHs) (Naphthalene) compounds. Soil samples were taken from 18 different sites polluted with oil wastes and cultured then obtained 312 isolated fungi from 64 replicates Primarily screening were done on fungal isolates on solid media containing naphthalene the results revealed that 25 fungal isolates gave good growth, 47 fungal isolates gave Moderate growth, 66 gave weak growth and 147 fungal isolates gave no growth on Naphthalene solid media.
Then secondary screening were done on 25 fungal is

Recent studies have proved the important role of fungi in the biodegradation of oil pollutants. The present study aims to find the optimal conditions for the fungi to get the best rate of the biodegradation of the polycyclic aromatic hydrocarbon (PAHs) (Naphthalene) compounds. Soil samples were taken from 18 different sites polluted with oil wastes and cultured then obtained 312 isolated fungi from 64 replicates Primarily screening were done on fungal isolates on solid media containing naphthalene the results revealed that 25 fungal isolates gave good growth, 47 fungal isolates gave Moderate growth, 66 gave weak growth and 147 fungal isolates gave no growth on Naphthalene solid media.
Then secondary screening were done on 25 fungal is

Our country faced lots of crises specially Wars and still living under the traumatic events. This would result in psychological disorder specially the Acute Stress Disorder (ASD). That’s if not treated, it will turn to be over Post Traumatic Stress Disorder(PTSD). Also not mentioning the shortage of recourses speaks about war and crises. That treat with its inflections psychologically and sociologically theses cases if happened.

The importance of this study arise through it is objective to introduce a program for EMDR which give benefit for treat in health, social, educational institutes.

Aims:

The objective of this Study is the identification of a Test the effectiveness of Eye Movement Desensi

This paper aims to find new analytical closed-forms to the  solutions of the nonhomogeneous functional differential equations of the n^th order with finite and constants delays and various initial delay conditions in terms of elementary functions using Laplace transform method. As well as, the definition of dynamical systems for ordinary differential equations is used to introduce the definition of dynamical systems for delay differential equations which contain multiple delays with a discussion of their dynamical properties: The exponential stability and strong stability

An optical spectroscopic study is reported in this article to study the correlation between the supermassive black hole (SMBH) and the star formation rate (SFR) for a sample of Seyfert galaxies type (I and II). The study focused on 45 galaxy of Seyfert 1, in addition to 45 galaxy of Seyfert 2, where these samples have been selected form different survey of Salon Digital Sky Survey (SDSS). The redshift (z) of these objects were between (0.02 – 0.26). The results of Seyfert 1 galaxies shows that there good correlation between the SMBH and the SFR depending on statistical analysis parameter named Spearman’s Rank Correlation in a factor of (ρ=0.609), as well as the Seyfert 2 galaxies results show a good correlation between the SMBH

An optical spectroscopic study is reported in this article to study the correlation between the supermassive black hole (SMBH) and the star formation rate (SFR) for a sample of Seyfert galaxies type (I and II). The study focused on 45 galaxy of Seyfert 1, in addition to 45 galaxy of Seyfert 2, where these samples have been selected form different survey of Salon Digital Sky Survey (SDSS). The redshift (z) of these objects were between (0.02 – 0.26). The results of Seyfert 1 galaxies shows that there good correlation between the SMBH and the SFR depending on statistical analysis parameter named Spearman’s Rank Correlation in a factor of (ρ=0.609), as well as the Seyfert 2 galaxies results show a good correlation between the SMBH and

In this paper the behavior of the quality of the gradient that implemented on an image as a function of noise error is presented. The cross correlation coefficient (ccc) between the derivative of the original image before and after introducing noise error shows dramatic decline compared with the corresponding images before taking derivatives. Mathematical equations have been constructed to control the relation between (ccc) and the noise parameter.