n the present work, a study is carried out to remove chromium (III) from
aqueous solution by: activated charcoal , attapulgite and date palm leaflet powder
(pinnae). The effect of various parameters such as contact time, and temperature has
been studied. The isotherm equilibrium data were well fitted by Freundlich and
Langmuir isotherm models. The adsorption capacity of chromium (III) that was
observed by activated charcoal , attapulgite and date palm leaflet powder (pinnae)
increased with the rise of temperature when the concentrations of Cr (III) were 600,
700 and 100mg/L respectively. The greatest adsorption capacity ofactivated
charcoal , attapulgite and date palm leaflet powder (pinnae) at 10°C was 7.51, 5.39
and 0.77mg.gˉ¹ respectively and reaching 9.99, 8.82 and 1.43mg.gˉ¹ at 37.5°C. The
thermodynamics study showed that the chromium (III) ions adsorption is
endothermic and spontaneous with the increase of randomness at the solid-solution
interface that involves adsorption and absorption mechanism.
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
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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
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A phytoremediation experiment was carried out with kerosene as a model for total petroleum hydrocarbons. A constructed wetland of barley was exposed to kerosene pollutants at varying concentrations (1, 2, and 3% v/v) in a subsurface flow (SSF) system. After a period of 42 days of exposure, it was found that the average ability to eliminate kerosene ranged from 56.5% to 61.2%, with the highest removal obtained at a kerosene concentration of 1% v/v. The analysis of kerosene at varying initial concentrations allowed the kinetics of kerosene to be fitted with the Grau model, which was closer than that with the zero order, first order, or second order kinetic models. The experimental study showed that the barley plant designed in a subsu
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A phytoremediation experiment was carried out with kerosene as a model for total petroleum hydrocarbons. A constructed wetland of barley was exposed to kerosene pollutants at varying concentrations (1, 2, and 3% v/v) in a subsurface flow (SSF) system. After a period of 42 days of exposure, it was found that the average ability to eliminate kerosene ranged from 56.5% to 61.2%, with the highest removal obtained at a kerosene concentration of 1% v/v. The analysis of kerosene at varying initial concentrations allowed the kinetics of kerosene to be fitted with the Grau model, which was closer than that with the zero order, first order, or second order kinetic models. The experimental study showed that the barley plant designed in a subsu
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Fire is the most sever environmental condition affecting on concrete structures, thus investigating for fire safet, IJSR, Call for Papers, Online Journal
Fire is the most sever environmental condition affecting on concrete structures, thus investigating for fire safety in structural concrete is important for building construction. The slow heat transfer and strength loss enables concrete to be effective for fire resistance. Concrete structures withstand when exposed to fire according to: their thermal properties, rate of heating, characteristic properties of concrete mixes and their composition and on the duration of fire, and concerned as thermal property with other factors such as loss of mass which affected by aggregate type, moisture content, and composition of concrete mix. The present research goal is to study the effect of rising temperature on the compressive strength of the rea
... Show MoreReactive Powder Concrete (RPC) is one of the most advanced recent high compressive strength concrete. This work explored the effects of using glass waste as a fractional replacement for fine aggregate in reactive powder concrete at levels of 0%, 25%, 50%, and 100%. Linear and mass attenuation coefficients have been calculated as a function of the sample's thickness and bremsstrahlung energy. These coefficients were obtained using energy selective scintillation response to bremsstrahlung having an energy ranging from (0.1-1.1) MeV. In addition, the half-value thickness of the samples prepared has been investigated. It was found that there is a reversal association between the attenuation coefficient and the energy of the bremsstrahlu
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