This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

Chitosan-schiff base with three different ratios of para-Dimethyl aminobenzaldehyde& chitosan Schiff base hydrogels have been prepared for controlled drug release study. The synthesized chitosan Schiff base and chitosan Schiff base hydrogel were characterized by FT-IR, UV-Visible, SEM, analysis. Swelling properties of the hydrogel were investigated at three different media pH (2, 7, 10). The swelling degree varied with the pH, amount of crosslinking agent glutaraldehyde and with the amount of paraDimethylaminobenzaldehyde for the hydrogels. All hydrogels were used for controlled drug release system. Aspirin was used as model drug, in three different buffer solution (2, 7, 10) as release media. The rate of release of drugs in the pH2 is m

 Abstract

This paper is an experimental work to determinate the effect of welding velocity and formed arc energy for CO2-MAG fusion weld pool. The input parameters (arc voltage, wire feed speed and gas flow rate) were investigated to find their effects on the weld joint efficiency. Design of experiment with response surface methodology technique was used to build empirical mathematical models for welding velocity and arc energy in term of the input welding parameters. The predicted quadratic models were statistically checked for adequacy purpose by ANOVA analysis. Additionally, numerical optimization was conducted to obtain the optimum values for welding velocity and arc energy. A good agree

This paper predicts the resilient modulus (Mr) for warm mix asphalt (WMA) mixtures prepared using aspha-min. Various predictor variables were analyzed, including asphalt cement types, asphalt contents, nominal maximum aggregate sizes (NMAS), filler content, test temperatures, and loading times. Univariate and multivariate analyses were conducted to examine the behavior of each predictor variable individually and collectively. Through univariate analysis, it was observed that Mr exhibited an inverse trend with asphalt cement grade, NMAS, test temperature, and load duration. Although Mr increased slightly with higher filler and asphalt content, the magnitude of this increase was minimal. Multivariate analysis revealed that the rate of change

This study examined >140 relevant publications from the last few years (2018–2021). In this study, classification was reviewed depending on the operation's progress. Electrocoagulation (EC), electrooxidation (EO), electroflotation (EF), electrodialysis (ED), and electro-Fenton (EFN) processes have received considerable attention. The type of action (individual or hybrid) for each electrochemical procedure was evaluated, and statistical analysis was performed to compare them as a new manner of reviewing cited papers providing a massive amount of information efficiently to the readers. Individual or hybrid operation progress of the electrochemical techniques is critical issues. Their design, operation, and maintenance costs vary depending o

Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st