The present study intends to prepare nanofibers mat of polyacrylonitrile by electrospinning technique and investigates their adsorption capacity to Congo red dye from the aqueous solution, after characterize it by different techniques such as FTIR, SEM, EDA, XRD and BET. The influence factors on adsorption were studied including adsorbent dosage, initial concentration, contact time, pH and ionic strength. The results confirmed that the increasing in pH decreases the adsorption capacity. So, the optimum adsorbent dosage, initial concentration and contact time were 0.006 g, 25 mg/L and 150 min respectively. The isotherm models of Freundlich and Langmuir were applied on the experimental adsorption data to evaluate the maximum capacity and energy of adsorption. The experimental data was founded more fitted with Langmuir model. Additional, the thermodynamic parameter changes such ∆G, ∆H and ∆S of adsorption were estimated. The results explained that the adsorption process was exothermic and nonspontaneous.
The aim of this study is to shed light on the importance of biofuels as an alternative to conventional energy, in addition to the importance of preserving agricultural crops, which are the main source of this fuel, to maintain food security, especially in developing countries. The increase in global oil prices, in addition to the fear of global warming, are among the main factors that draw the world’s attention to searching for alternative sources of traditional energy, which are sustainable on the one hand, and on the other hand reduce carbon emissions. Therefore, the volume of global investment in renewable energy in general, and in liquid biofuels and biomass in particular, has increased. Global fears emerged that the excessive
... Show MoreThis study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat
... Show MoreThis research aims at studying the relation between fair value and the Financial Reports Quality to achieve a number of aims such as :-
1- Throw light on the problems of the measurement that depends on the historic cost as it paves the way towards the method of the fair value in the accounting measurement.
2-Give a general definition for fair value in the accounting via analyzing the theoretical aspects that relates the subject and the scientific bases on which the relating accounting treatment depend.
3- Exhibit the characteristics that could be added by the fair value to the accounting Information .
The study problem is summarized in that the e
... Show MoreIn this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database
One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th
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