In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

This study involved the treatment of textile wastewater contaminated with direct blue 15 dye (DB15) using a heterogeneous photo-Fenton-like process. Bimetallic iron/copper nanoparticles loaded on bentonite clay were used as heterogeneous catalysts and prepared via liquid-phase reduction method using eucalyptus leaves extract (E-Fe/Cu@BNPs). Characterization methods were applied to resultant particles (NPs), including SEM, BET, and FTIR techniques. The prepared NPs were found with porous and spherical shapes with a specific surface area of particles was 28.589 m2/g. The effect of main parameters on the photo-Fenton-like degradation of DB15 was investigated through batch and continuous fixed-bed systems. In batch mode, pH, H2O2 dosage, DB15 c

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

The adsorption process of reactive blue 49 (RB49) dye and reactive red 195 (RR195) dye from an aqueous solutions was explored using a novel adsorbent produced from the sunflower husks encapsulated with copper oxide nanoparticle (CSFH). Primarily, the features of a CSFH, such as surface morphology, functional groups, and structure, were characterized. It was determined that coating the sunflower husks with copper oxide nanoparticles greatly improved the surface and structural properties related to the adsorption capacity. The adsorption process was successful, with a removal efficiency of 97% for RB49 and 98% for RR195 under optimal operating conditions, contact time of 180 min, pH of 7, agitation speed of 150 rpm, initial dye concentration

Heavy metal consider as major environmental pollutants. Many of industrial wastewater effluents contain a wide range of these heavy metals. The adsorption of Cd2+ and Pb2+ metal ions from aqueous solution by activated carbon was studied. The results showed that maximum adsorption capacity occurred at 486.9×10-3 mg/kg for Pb2+ ion and 548.8×10-3 mg/kg for Cd2+ ion. The adsorption in a mixture of the metal ions had a balancing effect on the adsorption capacity of the activated carbon. The adsorption capacity of each metal ion was affected by the presence of other metal ions rather than its presence individually. The study showed the presence of other heavy metals attribute to the reduction in the activated carbon capacity, and the adsorp

Etoricoxib (EXB) is a highly selective cox-2 inhibitor which belongs to the non-steroidal anti-inflammatory drug (NSAID). EXB is a class II drug according to the biopharmaceutical classification system (BCS), which possess a very low aqueous solubility in water.  In the present study, many trials were made to improve the aqueous solubility and dissolution rate of EXB by solid dispersion technique.

Eighteenth EXB formulas were formulated as a solid dispersion using a variety of hydrophilic polymers (as carriers)   including poloxamer 407 (PXM 407), poloxamer 188 (PXM 188) and polyethylene glycol 4000 (PEG 4000) at different drug: polymer ratios (1:1, 1:3 and 1:5). These formulas were prepared by two methods; solvent

Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so