Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

Single Walled Carbon nanotubes (SWCNTs), as nano-needle structures, are good candidates as nanocarrier delivery systems that carry drug to the site of action. They are good due to their unique pharmaceutical properties. Teniposide is an anticancer drug, which is widely used, but it has a problem of low solubility. In this study, to improve the properties of carbon nanotubes, pre-functionalization of carbon nanotubes via carboxylation with strong acids has been performed and then functionalized through attaching them to the polymer and copolymer. Concurrently, a proper polymer-copolymer combination has been selected by the UV-Visible spectrometer at 880nm. It is selected based on the qualitative dispersibility analysis, the visual observa

Meaning letters in Arabic are characterized by the diversity and abundance of their linguistic material, and are also distinguished by their large number and types, to the point that some of them have reached a hundred letters confined to five categories

Incivility in nursing education can negatively affect the academic achievement. As there is no tool in Arabic to assess incivility among nursing students, there is a need for a valid and reliable tool.

Background:sThe aims of this study were to evaluate and compare the ability of three different techniques to obdurate simulated lateral canals, evaluate the effect of the main canal curvature on obturation of lateral canals and compare the gutta-percha penetration between coronal and apical lateral canals. Materials and methods: Resin blocks with 30 straight and 30 curved were used in this study. Each canal has two parallel lateral canals. The main canal has 0.3 mm apical diameter and 0.04 taper. The canals were divided into six groups according to canal curvature and obturation techniques used (n=10): Groups C1 and C2: straight and curved canals obturated with continuous wave technique using E&Q masterTM system. Groups O1 and O2: straight

Pollutants generation is strongly dependant on the firing temperature and reaction rates of the gaseous reactants in the gas turbine combustion chamber. An experimental study is conducted on a two-shaft T200D micro-gas turbine engine in order to evaluate the impact of injecting ethanol directly into the compressor inlet air on the exhaust emissions. The study is carried out in constant speed and constant load engine tests. Generally, the results showed that when ethanol was added in a concentration of 20% by volume of fuel flow; NO_x emission was reduced by the half, while CO and UHC emissions were almost doubled with respect to their levels when burning conventional LPG fuel alone.

In the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to