In this paper, variable gain nonlinear PD and PI fuzzy logic controllers are designed and the effect of the variable gain characteristic of these controllers is analyzed to show its contribution in enhancing the performance of the closed loop system over a conventional linear PID controller. Simulation results and time domain performance characteristics show how these fuzzy controllers outperform the conventional PID controller when used to control a nonlinear plant and a plant that has time delay.

In this study, a packed bed was used to remove pathogenic bacteria from synthetic contaminated water. Two types of packing material substrates, sand and zeolite, were used. These substrates were coated with silver nanoparticles (AgNPs), which were prepared by decomposition of Ag ions from AgNO3 solution. The prepared coated packings were characterized using scanning electron microscopy, energy-dispersive X-ray spectroscopy and transmission electron microscopy. The packed column consisted of a PVC cylinder of 2 cm diameter and 20 cm in length. The column was packed with silver nanoparticlecoated substrates (sand or zeolite) at a depth of 10 cm. Four types of bacteria were studied: Escherichia coli, Shigella dysenteriae, Pseudomonas aerugi

In this study, condensation polymerization was used to synthesize a number of novel liquid crystal polymers with 1,3,4-oxadiazole rings based on melamine. The new synthesized polymers were characterized by Fourier transform infrared (FTIR) and proton nuclear magnetic resonance (1HNMR) spectroscopy. Differential scanning calorimetry (DSC) and optical polarization microscopy (OPM) were used to investigate their liquid crystalline properties. The results demonstrated that throughout a wide temperature range, most of the polymers exhibited columnar (CohX) and nematic (N) liquid crystalline phases.

Background: Bacteriocin is a peptidic toxin has many advantages to bacteria in their ecological niche and has strong antibacterial activity. Objective: The aim of this study was to evaluation of bacteriocin using Streptococcus sanguinis isolated from human dental caries.

Subjects and Methods: Thirty five streptococcus isolates were diagnosed and tested for their production of bacteriocin, and then the optimal conditions for production of bacteriocin were determined.  After that, the purification of bacteriocin was made partially by ammonium sulfate at 95% saturation levels, followed by and gel filtration chromatography

This study included the isolation and identification of Aspergillus flavus isolates associated with imported American rice grains and local corn grains which collected from local markets, using UV light with 365 nm wave length and different media (PDA, YEA, COA, and CDA ). One hundred and seven fungal isolates were identified in rice and 147 isolates in corn.4 genera and 7 species were associated with grains, the genera were Aspergillus ,Fusarium ,Neurospora ,Penicillium . Aspergillus was dominant with occurrence of 0.47% and frequency of 11.75% in rice grains whereas in corn grains the genus Neurospora was dominant with occurrence of 1.09% and frequency 27.25% ,results revealed that 20 isolates out of 50 A. flavus isolates were able

Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t

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