In this paper, first and second order sliding mode controllers are designed for a single link robotic arm actuated by two Pneumatic Artificial Muscles (PAMs). A new mathematical model for the arm has been developed based on the model of large scale pneumatic muscle actuator model. Uncertainty in parameters has been presented and tested for the two controllers. The simulation results of the second-order sliding mode controller proves to have a low tracking error and chattering effect as compared to the first order one. The verification has been done by using MATLAB and Simulink software.

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Understanding the effects of fear, quadratic fixed effort harvesting, and predator-dependent refuge are essential topics in ecology. Accordingly, a modified Leslie–Gower prey–predator model incorporating these biological factors is mathematically modeled using the Beddington–DeAngelis type of functional response to describe the predation processes. The model’s qualitative features are investigated, including local equilibria stability, permanence, and global stability. Bifurcation analysis is carried out on the temporal model to identify local bifurcations such as transcritical, saddle-node, and Hopf bifurcation. A comprehensive numerical inquiry is carried out using MATLAB to verify the obtained theoretical findings and und

   A microbubble air flotation technique was used to remove chromium ions from simulated wastewater (e.g. water used for electroplating, textiles, paints and pigments, and tanning leather). Experimental parameters were investigated to analyze the flotation process and determine the removal efficiency. These parameters included the location of the sampling port from the bottom of the column, where the diffuser is located to the top of flotation column (30, 60, and 90 cm), the type of surfactant (anionic, SDS, or cationic, CTAB) and its concentration (5, 10, 15, and 20 mg/L), the pH of the initial solution (3, 5, 7, 9, and 11), the initial contaminant concentration (10, 20, 30, and 40 mg/L), the gas flow rate (0.1, 0.2, 0.3, and 0.5 L/mi

This work was conducted to study the extraction of eucalyptus oil from natural plants (Eucalyptus camaldulensis leaves) using water distillation method by Clevenger apparatus. The effects of main operating parameters were studied: time to reach equilibrium, temperature (70 to100°C), solvent to solid ratio (4:1 to 8:1 (v/w)), agitation speed (0 to 900 rpm), and particle size (0.5 to 2.5 cm) of the fresh leaves, to find the best processing conditions for achieving maximum oil yield. The results showed that the agitation speed of 900 rpm, temperature 100° C, with solvent to solid ratio 5:1 (v/w) of particle size 0.5 cm for 160 minute give the highest percentage of oil (46.25 wt.%). The extracted oil was examined by HPLC.

Selective recovery of atropine from Datura innoxia seeds was studied. Applying pertraction in a rotating film contactor (RFC) the alkaloid was successfully recovered from native aqueous extracts obtained from the plant seeds. Decane as a liquid membrane and sulfuric acid as a stripping agent were used. Pertraction from native liquid extracts provided also a good atropine refinement, since the most of co-extracted from the plant species remained in the feed or membrane solution. Solid–liquid extraction of atropine from Datura innoxia seeds was coupled with RF-pertraction in order to purify simultaneously the extract obtained from the plant. Applying the integrated process, proposed in this study, a product containing 92.6% atropine was

A mixture of algae biomass (Chrysophyta, Cyanophyta, and Chlorophyte) has been investigated for its possible adsorption removal of cationic dyes (methylene blue, MB). Effect of pH (1-8), biosorbent dosage (0.2-2 g/100ml), agitated speed (100-300), particle size (1304-89μm), temperature (20-40˚C), initial dye concentration (20-300 mg/L), and sorption–desorption were investigated to assess the algal-dye sorption mechanism. Different pre-treatments, alkali, protonation, and CaCl2 have been experienced in order to enhance the adsorption capacity as well as the stability of the algal biomass. Equilibrium isotherm data were analyzed using Langmuir, Freundlich, and Temkin models. The maximum dye-sorption capacity was 26.65 mg/g at pH= 5, 25

The high cost of chemical analysis of water has necessitated various researches into finding alternative method of determining portable water quality. This paper is aimed at modelling the turbidity value as a water quality parameter. Mathematical models for turbidity removal were developed based on the relationships between water turbidity and other water criteria. Results showed that the turbidity of water is the cumulative effect of the individual parameters/factors affecting the system. A model equation for the evaluation and prediction of a clarifier’s performance was developed:

Model: T = T₀(-1.36729 + 0.037101∙10^λpH + 0.048928t + 0.00741387∙alk)

The developed model will aid the predictiv