In this study, (50–110 nm) magnetic iron oxide (α-Fe2O3) nanoparticles were synthesized by pulsed laser ablation of iron target in dimethylformamide (DMF) and sodium dodecyl sulfate (SDS) solutions. The structural properties of the synthesized nanoparticles were investigated by using Fourier Transform Infrared (FT-IR) spectroscopy, UV–VIS absorption, scanning electron microscopy (SEM), atomic force microscopy (AFM), and X-ray diffraction (XRD). The effect of laser fluence on the characteristics of these nanoparticles was studied. Antibacterial activities of iron oxide nanoparticles were tested against Gram-positive; Staphylococcus aureus and Gram-negative; Escherichia coli, Pseudomonas aeruginosa and Serratia marcescens. The results sh

The research involves preparing gold nanoparticles (AuNPs) and studying the factors that influence the shape, sizes and distribution ratio of the prepared particles according to Turkevich method. These factors include (reaction temperature, initial heating, concentration of gold ions, concentration and quantity of added citrate, reaction time and order of reactant addition). Gold nanoparticles prepared were characterized by the following measurements: UV-Visible spectroscopy, X-ray diffraction and scanning electron microscopy. The average size of gold nanoparticles was formed in the range (20 -35) nm. The amount of added citrate was changed and studied. In addition, the concentration of added gold ions was changed and the calibration cur

Abstract

This paper discusses the essence of the developmental process in auditing firms and offices at the world today. This process is focused on how to adopt the audit concepts which is based on Information and Communication Technology (ICT), including the Continuous Auditing (CA) in particular. The purpose of this paper is to design a practical model for the adoption of CA and its requirements according to the Technology Acceptance Model (TAM). This model will serve as a road map for manage the change and development in the Iraqi auditing firms and offices. The paper uses the analytical approach in reaching to the target results. We design the logical and systematic relations between the nine variable

This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete

Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signa