Esterification considers the most important reaction in biodiesel production. In this study, oleic acid was used as a suggested feedstock in order to study and simulate production of biodiesel. The batch esterification reaction of oleic acid was carried out at various operating conditions; temperature from 40 to 70 °C, ethanol to oleic acid molar ratio from 3/1 and 6/1 and a reaction time up to 180 min.
The catalyst used was prepared NaY zeolite, which is added to the reaction mixture as 2, 5 and 10 wt.% of oleic acid.
The results show that the optimum conditions, gives 0.81 conversion of oleic acid, were 6/1 molar ratio of ethanol/oleic acid, 5 wt.% NaY relative to initial oleic acid, 70°C and 60 minutes. The activation energy o

Polyaniline nanofibers (PAni-NFs) have been synthesized under various concentrations (0.12, 0.16, and 0.2 g/l) of aniline and different times (2h and 3 h) by hydrothermal method at 90°C. Was conducted with the use of X-ray diffraction (XRD), Fourier Transform Infrared spectra (FTIR), Ultraviolet-Visible (UV-VIS) absorption spectra, Thermogravimetric Analysis (TGA), and Field Emission-Scanning Electron Microscopy (FE-SEM). The X-ray diffraction patterns revealed the amorphous nature of all the produced samples. FE-SEM demonstrated that Polyaniline has a nanofiber-like structure. The observed typical peaks of PAni were (1580, 1300-1240, and 821 cm-1 ), analyzed by the chemical bonding of the formed PAni through FTIR spectroscopy. Also, tests

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

An International Publisher for Academic and Scientific Journals The mucilage of white and black chia seeds were extracted and determining their contents of bioactive compounds such as tannins, glycosides, flavonoids, phenols, and studying their activity as anti-filamentary and anticancer. Results showed that tannins exist in white chia seeds with 35%while it is 38% in black seeds, flavonoids represent 0.98mg/ml in white chia seeds and 1.5 mg/ml for black seeds. Both kinds of seeds showed anti-filamentaryactivity, the inhibition ratio was 86.5% for white seeds and 97.3% for black seeds. Chia black seeds showed anticancer activity and the inhibition of the tumor muscle cell line ratio (GI%) was 34.8% at 50mg/ml concentration and 88.4%

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

The catalytic activity of faujasite type NaY catalysts prepared from local clay (kaolin) with different Si/Al ratio was studied using cumene cracking as a model for catalytic cracking process in the temperature range of 450-525° C, weight hourly space velocity (WHSV) of 5-20 h1, particle size ≤75μm and atmospheric pressure. The catalytic activity was investigated using experimental laboratory plant scale of fluidized bed reactor.
It was found that the cumene conversion increases with increasing temperature and decreasing WHSV. At 525° C and WHSV 5 h-1, the conversion was 42.36 and 35.43 mol% for catalyst with 3.54 Si/Al ratio and Catalyst with 5.75 Si/Al ratio, respectively, while at 450° C and at the same WHSV, the conversion w

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

      TV medium derives its formal shape from the technological development taking place in all scientific fields, which are creatively fused in the image of the television, which consists mainly of various visual levels and formations. But by the new decade of the second millennium, the television medium and mainly (drama) became looking for that paradigm shift in the aesthetic formal innovative fields and the advanced expressive performative fields that enable it to develop in treating what was impossible to visualize previously. In the meantime, presenting what is new and innovative in the field of unprecedented and even the familiar objective and intellectual treatments. Thus the TV medium has sought for work