In this study, nanocomposites have been prepared by adding
multiwall carbon nanotubes (MWCNTs) with weight ratios (0, 2, 3,
4, 5) wt% to epoxy resin. The samples were prepared by hand lay-up
method. Influence of an applied load before and after immersion in
sodium hydroxide (NaOH) of normality (0.3N) for (15 days) at
laboratory temperature on wear rate of Ep/MWCNTs
nanocomposites was studied. The results showed that wear rate
increases with increasing the applied load for the as prepared and
immersed samples and after immersion. It was also found that epoxy
resin reinforced with MWCNTs has wear rate less than neat epoxy.
The sample (Ep + 5wt% of MWCNTs) has lower wear rate. The
immersion effect in base so

In this work, polyvinylpyrrolidone (PVP)/ Multi-walled carbon nanotubes (MWCNTs) nanocomposites were prepared with two concentrations of MWCNTs by casting method. Morphological, structural characteristics and electrical properties were investigated. The state of MWCNTs dispersion in a PVP matrix was indicated by Field Effect-Scanning Electron Microscopy (FESEM) which showed a uniform dispersion of MWCNTs within the PVP matrix. X-ray Diffraction (XRD) indicate strong bonding of carbonyl groups of PVP composite chains with MWCNTs. Fourier transfer infrared (FTIR) studies shows characteristics of various stretching and bending vibration bands, as well as shifts in some band locations and intensity changes in others. Hall effect was stu

Abstract

 The objective of image fusion is to merge multiple sources of images together in such a way that the final representation contains higher amount of useful information than any input one.. In this paper, a weighted average fusion method is proposed. It depends on using weights that are extracted from source images using counterlet transform. The extraction method is done by making the approximated transformed coefficients equal to zero, then taking the inverse counterlet transform to get the details of the images to be fused. The performance of the proposed algorithm has been verified on several grey scale and color test  images, and compared with some present methods.

In this work we experimentally investigated SWCNTs and MWCNTs to increase their thermal conductivity and electrically functionalization process using different reagents ((nitric acid, HNO3 followed by acid treatment with H2SO4), then washed with deionized water (DW) and then treated with H2O2 via ultrasonic technique. Then repeated the steps with MWCNTs and compare their results in an effort to improve experimental conditions that efficiently differentiate the surface of the single walled carbon nanotubes (SWCNTs) and multi walled carbon nanotubesi(MWCNTs) that less nanotubes destroy and to enhance the properties of them and also to reduce aggregation in liquid. the results were prove by XRD, and infrared spectroscopy (FTIR). The FTIR sp

 This paper comprises the design and operation of mono-static backscatter lidar station based on a pulsed Nd: YAG laser that operates at multiple wavelengths. The three-color lidar laser transmitter is based on the collinear fundamental 1064 nm, second harmonic 532 nm and a third harmonic 355nm output of a Nd:YAG laser. The most important parameter of lidar especially daytime operations is the signal-to-noise ratio (SNR) which gives some instructions in designing of lidar and it is often limit the effective range. The reason is that noises or interferences always badly affect the measured results. The inversion algorithms have been developed for the study of atmospheric aerosols. Signal-to-noise ratio (SNR) of three-color channel re

This paper tackles with principal component analysis method (PCA ) to dimensionality reduction in the case of linear combinations to digital image processing and analysis. The PCA is statistical technique that shrinkages a multivariate data set consisting of inter-correlated variables into a data set consisting of variables that are uncorrelated linear combination, while ensuring the least possible loss of useful information. This method was applied to a group of satellite images of a certain area in the province of Basra, which represents the mouth of the Tigris and Euphrates rivers in the Shatt al-Arab in the province of Basra.

One of the challenges faced by traditional intrusion detection systems based on machine learning or deep learning is instability when dealing with unbalanced network traffic, leading to failure in detecting certain attacks (minority classifications). Additionally, they struggle with multi-stage attacks, resulting in an increase in false alarms. This paper presents a hierarchical intrusion detection system supported by a Prediction Verification Layer (PVL) and a Feature Inheritance Mechanism (FIM). Where PVL contributes to documenting the system’s final decision and increasing sensitivity to minority attacks, FIM also helps in inheriting features from previous layers and correcting errors as much as possible. Additionally, it allows for ad