Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

In this work, multilayer nanostructures were prepared from two metal oxide thin films by dc reactive magnetron sputtering technique. These metal oxide were nickel oxide (NiO) and titanium dioxide (TiO2). The prepared nanostructures showed high structural purity as confirmed by the spectroscopic and structural characterization tests, mainly FTIR, XRD and EDX. This feature may be attributed to the fine control of operation parameters of dc reactive magnetron sputtering system as well as the preparation conditions using the same system. The nanostructures prepared in this work can be successfully used for the fabrication of nanodevices for photonics and optoelectronics requiring highly-pure nanomaterials.

In this work, enhancement to the fluorescence characteristics of laser dye solutions hosting highly-pure titanium dioxide nanoparticles as random gain media. This was achieved by coating two opposite sides of the cells containing these media with nanostructured thin films of highly-pure titanium dioxide. Two laser dyes; Rhodamine B and Coumarin 102, were used to prepare solutions in hexanol and methanol, respectively, as hosts for the nanoparticles. The nanoparticles and thin films were prepared by dc reactive magnetron sputtering technique. The enhancement was observed by the narrowing of fluorescence linewidth as well as by increasing the fluorescence intensity. These parameters were compared to those of the dye only and the dye solution

Trickle irrigation is a system for supplying filtered water and fertilizer directly into the soil and water and it is allowed to dissipate under low pressure in an exact predetermined pattern. An equation to estimate the wetted area of unsaturated soil with water uptake by roots is simulated numerically using the HYDRUS-2D/3D software. In this paper, two soil types, which were different in saturated hydraulic conductivity were used with two types of crops tomato and corn, different values of emitter discharge and initial volumetric soil moisture content were assumed. It was assumed that the water uptake by roots was presented as a continuous sink function and it was introduced into Richard's equation in the unsaturated z

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Protection of the oil pipelineswhich extracted from the wells was found to shut the well and prevent the leakage of oil when broken using safety valve. This valve is automatically activated by loss of pressure between the well and pipelines, which take the pressure, signal from hydraulic pressure sensor through pressure control valve which has constant or variable value but it is regulated manually. The manual regulatory process requires the presence of monitoring workers continuously near the wells which are always found in remote areas. In this paper, a smart system has been proposed that work with proportional pressure control valve and also electronic pressure sensor through Arduino controller, which is programmed in a way that satisfie

In this study, the potential of adsorption of amoxicillin antibiotic (AMOX) from aqueous solutions using prepared activated carbon (AC) was studied. The used AC was prepared from an inexpensive and available precursor (sunflower seed hulls (SSH)) and activated by potassium hydroxide (KOH). The prepared AC was examined for its ability to remove AMOX from aqueous contaminated solutions and characterized with the aid of N2 -adsorption/desorption isotherm Brunauer–Emmett– Teller, scanning electron microscopy, energy-dispersive X-ray spectroscopy and Fourier-transform infrared. Zeta potential of the prepared activated carbon from sunflower seed hulls (SSHAC) were studied in relation to AMOX adsorption. The physical and chemical propert

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve