In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the developing system is consist of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny

Waste recycling is one of the modern means of treating waste and minimizing its harmful effects that have caused problems for all countries of the world through the disposal of them in a safe and healthy manner as well as achieving economic and social benefits to the United Nations, and through the goals of sustainable development. 2015-2013 seeks to solve the environmental problems, including various peoples of the world, through various projects and programs, including waste recycling. Here is the question of whether there is a relationship between waste recycling and the goals of sustainable development, the research seeks to answer through five categories to determine the type of relationship between waste recycling and the g

Objectives: Bromelain is a potent proteolytic enzyme that has a unique functionality makes it valuable for various therapeutic purposes. This study aimed to develop three novel formulations based on bromelain to be used as chemomechanical caries removal agents. Methods: The novel agents were prepared using different concentrations of bromelain (10–40 wt. %), with and without 0.1–0.3 wt. % chloramine T or 0.5–1.5 wt. % chlorhexidine (CHX). Based on the enzymatic activity test, three formulations were selected; 30 % bromelain (F1), 30 % bromelain-0.1 % chloramine (F2) and 30 % bromelain-1.5 % CHX (F3). The assessments included molecular docking, Fourier-transform infrared spectroscopy (FTIR), viscosity and pH measurements. The efficie

Objectives Bromelain is a potent proteolytic enzyme that has a unique functionality makes it valuable for various therapeutic purposes. This study aimed to develop three novel formulations based on bromelain to be used as chemomechanical caries removal agents. Methods The novel agents were prepared using different concentrations of bromelain (10–40 wt. %), with and without 0.1–0.3 wt. % chloramine T or 0.5–1.5 wt. % chlorhexidine (CHX). Based on the enzymatic activity test, three formulations were selected; 30 % bromelain (F1), 30 % bromelain-0.1 % chloramine (F2) and 30 % bromelain-1.5 % CHX (F3). The assessments included molecular docking, Fourier-transform infrared spectroscopy (FTIR), viscosity and pH measurements. The efficiency

Authors in this work design efficient neural networks, which are based on the modified Levenberg - Marquardt (LM) training algorithms to solve non-linear fourth - order three -dimensional partial differential equations in the two kinds in the periodic and in the non-periodic - Periodic. Software reliability growth models are essential tools for monitoring and evaluating the evolution of software reliability. Software defect detection events that occur during testing and operation are often treated as counting processes in many current models. However, when working with large software systems, the error detection process should be viewed as a random process with a continuous state space, since the number of faults found during testin

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an