The influence of dye laser Rhodamine 6G (R6G) on the molecular structure of silica aerogel prepared by normal drying method is reported. The study also tests the effect of dye concentration on morphological and physical properties. Fourier Transform Infrared Spectroscopy (FTIR) was used to examine this effect, in addition to Field Emission Scanning Electron Microscopy (FESEM), contact angle, and surface area measurement. It was found from FTIR data that the dye laser stays with the inner structure of samples and, at high concentration, it gives a good influence by reducing (OH) band and increasing (CH) band, leading to changing the contact angle from (123^á´¼) to (145^á´¼). Whereas particle size varied from 22 n

     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from

     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant

Abstract Background: The daily usage of maxillofacial prostheses causes them to mechanically deteriorate with time. This study was aimed to evaluate the reinforcement of VST50F maxillofacial silicone by using yttrium oxide (Y2O3) nanoparticles (NPs) to resist aging and mechanical deterioration. Materials and Method: Y2O3 NPs (30–45nm) were loaded into VST50F maxillofacial silicone in two weight percentages (1 and 1.5 wt%), which were predetermined in a pilot study as the best rates for improving tear strength with minimum increase in hardness values. A total of 120 specimens were prepared and divided into the control and experimental groups (with 1 and 1.5 wt% Y2O3 addition). Each group included 40 specimens, 10 specimens for each paramet

     Serious gases have been highly related to being prejudiced against human life within the environment. The evolution of a trustworthy gas sensor with an elevated response is of major importance for detecting various hazardous gases. Titanium dioxide (TiO₂) nanotubes (TNTs) are favorable candidates with considerable potential and stellar performance in gas sensor applications. In this work, we have studied the effect of voltage on preparing TiO₂ nanotubular arrays via the anodization technique for gas sensor applications. A simple electrochemical anodization approach was used to synthesize titanium dioxide nanotubes. Diverse techniques of characterization were used to evaluate TNTs. The results gained from fi

This research prepared polymer blend contains from epoxy resin (Ep) and polyurethane
)Pu) as a matrix material of percentage (90 %) from epoxy and ) 10 (% polyurethane and
reinforced by PVC fibers and aluminum fibers two dimension knitted mat with fractional
volume(15 %), and study impact strength before and after reinforcing at temperatures of
(20,40,60(
o
CØŒand the results have shown that the reinforcing matrix materials by fibers
increased impact strength values that rise from(3.387kJ/m2) to (151.62kJ/m2) of composite
material (Ep+Pu+PVC(and thus ) Ep+Pu+PVC+Al.F) at last (Ep+Pu+Al.F (. following
composite material so that temperatures increase led to rise impact strength values except the
polymer

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

      Wireless sensor network (WSN) security is an important component for protecting data from an attacker. For improving security, cryptography technologies are divided into two kinds: symmetric and asymmetric. Therefore, the implementation of protocols for generating a secret key takes a long time in comparison to the sensor’s limitations, which  decrease network throughput because they are based on an asymmetric method. The asymmetric algorithms are complex and decrease network throughput. In this paper, an encryption symmetric secret key in wireless sensor networks (WSN) is proposed. In this work, 24 experiments are proposed, which are encryption using the AES algorithm in the cases of 1 key, 10 keys, 25 keys, and 50 keys. I