Finding a new source of resistance is important to reduce the use of synthetic pesticides, which can meet the global need of suppressing pollution. In this study, the resistance of eight eggplant cultivars to Aphis gossypii was evaluated. Results of the current study highlighted that the cultivar Long-Green has a very strong resistance after 14 days post infestation whereas Pearl-Round and White-Casper cultivars were susceptible. The rest of the tested cultivars (Green-oblong, Purple-panter, Paris, Ashbilia, and Barcelona) had mild resistance. Also, the study found significant differences between the infested and non-infested plants among the tested cultivars in the plant’s height, fresh-, and dry-weight. The susceptible cultivars

In the current research, we investigated the absorption spectrum for R590 and C480 dyes in ethanol solvent for different dye solution concentrations of 10-4, 10-5 and 10-6M. These dyes have been prepared and studied before and after gamma irradiation (first, second ionization) using cesium-137 source with absorbed doses of 18.36 Gy (time exposure of 10 days) and 73.44 Gy (with time exposure of 40 days). We noticed that the absorption intensity was decreased with decreasing concentration, before gamma irradiation while the absorption spectrum peak shifted towards the short wavelength (blue shift). It was also found that the intensity of absorption spectrum increased and shifted the absorption spectrum peak towards the long wavelength (red

This paper presents the design and analysis of composite right left hand (CRLH) electromagnetic bandgap (EBG) structure. The proposed unit cell is consistent of a dielectric substrate with dimensions of 5×5×1 mm 3 made of FR4-Epoxy with εr = 4.4 underneath of a conductive patch with dimensions of 4.4×4.4mm 2 . The unit cell is structured to perform a negative permittivity (ε) and negative permeability (µ) in different bands. The proposed unit cell is developed to 5G systems in the sub-6GHz bands. In this work, a complete analysis of the unit cell in terms of Sparameters, constitutive parameters and refraction index are evaluated using HFSS simulation package based on Finite Element Method (FEM).

         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

Recent population studies have shown that placenta accreta spectrum (PAS) disorders remain undiagnosed before delivery in half to two-thirds of cases. In a series from specialist diagnostic units in the USA, around one-third of cases of PAS disorders were not diagnosed during pregnancy. Maternal