In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

Frictional resistance occurs whenever sliding happens, negatively impacting treatment outcomes and duration. It is a clinical challenge and must be dealt with efficiently to achieve the best orthodontic results. Aims of this study: compare and evaluate the static frictional forces under the wet condition to mimic the oral environment produced by using a polycrystalline ceramic bracket, monocrystalline ceramic bracket, 0.014 of an inch nickel-titanium (Rhodium coated archwires, and ilusio aesthetic archwires), and 0.019 x 0.025 of an inch stainless steel (Rhodium coated archwires, and ilusio aesthetic archwires). Ninety-six aesthetic brackets (48 monocrystalline and 48 polycrystalline brackets) were used and stored in different incub

Abstract: The article aimed to formulate an MLX binary ethosome hydrogel for topical delivery to escalate MLX solubility, facilitate dermal permeation, avoid systemic adverse events, and compare the permeation flux and efficacy with the classical type. MLX ethosomes were prepared using the hot method according to the Box–Behnken experimental design. The formulation was implemented according to 16 design formulas with four center points. Independent variables were (soya lecithin, ethanol, and propylene glycol concentrations) and dependent variables (vesicle size, dispersity index, encapsulation efficiency, and zeta potential). The design suggested the optimized formula (MLX−Ethos−OF) with the highest desirability to perform the

The aim of our study was to investigate the antiviral activity of the Corchorus olitorius family Tiliaceae cultivated in Iraq against measles virus, and to demonstrate an overview about chemical constituents and pharmacological activity of Corchorus olitorius L.

About150 gm Leaves of Corchorus. olitorius were defatted by maceration in hexane for 24 hrs. The defatted plant materials were subjected for extraction after filtration using Soxhlet apparatus, with aqueous methanol 85% as a solvent extraction for 24 hours, the extract was filtered, and the solvent was evaporated under reduced pressure using a rotary evaporator to get a dry extract of about 12 gm. About 4 gm from the residue was suspended in 100

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the