Metal oxide nanoparticles demonstrate uniqueness in various technical applications due to their suitable physiochemical properties. In particular, yttrium oxide nanoparticle(Y₂O₃NPs) is familiar for technical applications because of its higher dielectric constant and thermal stability. It is widely used as a host material for a variety of rare-earth dopants, biological imaging, and photodynamic therapies. In this investigation, yttrium oxide nanoparticles (Y₂O₃NPs) was used as an ecofriendly corrosion inhibitor through the use of scanning electron microscopy (SEM), Fourier transforms infrared spectroscopy (FT-IR), UV-Visible spectroscopy, X-ray diffraction (XRD), and energy dispersive X-ray spe

This paper presents the effect of relativistic and ponderomotive nonlinearity on cross-focusing of two intense laser beams in a collisionless and unmagnetized plasma. It should be noted here that while considering the self-focusing due to relativistic electron mass variation, the electron ponderomotive density depression in the channel may also be important. Therefore/these two nonlinearties may simultaneously affect the self-focusing process. These nonlinearities depend not only on the intensity of one laser but also on the second laser. Therefore, one laser beam affects the dynamics of the second beam and hence the process of cross-focusing takes place. The electric field amplitude of the excited electron plasma wave (EPW) has been cal

Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

Akaike’s Information Criterion (AIC) is a popular method for estimation the number of sources impinging on an array of sensors, which is a problem of great interest in several applications. The performance of AIC degrades under low Signal-to-Noise Ratio (SNR). This paper is concerned with the development and application of quadrature mirror filters (QMF) for improving the performance of AIC. A new system is proposed to estimate the number of sources by applying AIC to the outputs of filter bank consisting quadrature mirror filters (QMF). The proposed system can estimate the number of sources under low signal-to-noise ratio (SNR).

Image compression is a serious issue in computer storage and transmission,  that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the  mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless com

Euphrates River extends about 125 km within the study area located in Annassiriyah City, Dhi Qar Governorate, Iraq. The impact of the seven hydraulic structures on the discharge capacity of the Euphrates River needs to be considered. The main objectives of this research are to increase the discharge capacity of Euphrates River within Annassiriyah City during flood seasons and study the impact of these hydraulic structures on the river capacity by using HEC-RAS 5.0.3 software. Five scenarios were simulated to study the different current condition of Euphrates River within Annassiriyah City. Other additional four scenarios were implemented through river training to increase the river capacity to 1300 m³/s; it is the flood

This study intends to examine the efficiency of student-centered learning (SCL) through Google classroom in enhancing the readiness of fourth stage females’ pre-service teachers. The research employs a quasi-experimental design with a control and experimental group to compare the teaching readiness of participants before and after the intervention. The participants were 30 of fourth stage students at the University of Baghdad - College of Education for Women/the department of English and data were collected through observation checklist to assess their teaching experience and questionnaires to assess their perceptions towards using Google Classroom. Two sections were selected, C as a control group and D as the experimental one each with (

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the developing system is consist of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny Edge detection algo

A new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n