The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group of signatures, numbering 70 images, were used. Image preprocessing steps were performed on them, and their features were extracted using the median filter. After that, the eigenvector and eigenvalue were calculated using the PCA algorithm. Then the backpropagation neural network algorithm was applied for training and testing where the performance reached 6.7995e−07 for 82 epochs and the accuracy was 99.98%.
The azo ligand obtained from the diazotization reaction of 2-aminobenzothiazole and 4- nitroaniline yielded a novel series of complexes with Co(II), Ni(II), Cu(II), and Zn(II) ions. The complexes were investigated using spectral techniques such as UV-Vis, FT-IR, 1H and 13C NMR spectroscopic analyses, LC-MS and atomic absorption spectrometry, electrical conductivity, and magnetic susceptibility. The molar ratio of the synthesized compounds was determined using the ligand exchange ratio, which revealed the metal-ligand ratios in the isolated complexes were 1:2. The synthesized complexes were tested for antimicrobial activity against S. aureus, E. coli, C. albicans, and C. tropicalis bacterial species. Additionally, their binding affinities we
... Show MoreBackground: Ankylosing spondylitis is a chronic inflammatory disease that mostly involves the spine and sacroiliac joints. It is associated with a decreased quality of life. Biological medicines such as infliximab and its biosimilar are the mainstay treatments for active ankylosing spondylitis.
Objective: The study objective was to conduct a pharmacoeconomic study comparing the cost-effectiveness of the reference infliximab with its biosimilar in ankylosing spondylitis patients visiting public hospitals.
Subjects and Method: This is a two-center pharmacoeconomic study performed at two large teaching governmental hospitals in Baghdad, Iraq, which s
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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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
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In this paper, Pentacene based-organic field effect transistors (OFETs) by using different layers (monolayer, bilayer and trilayer) for three different gate insulators (ZrO2, PVA and CYEPL) were studied its current–voltage (I-V) characteristics by using the gradual-channel approximation model. The device exhibits a typical output curve of a field-effect transistor (FET). Source-drain voltage (Vds) was also investigated to study the effects of gate dielectric on electrical performance for OFET. The effect of capacitance semiconductor in performance OFETs was considered. The values of current and transconductance which calculated using MATLAB simulation. It exhibited a value of current increase with increasing source-drain voltage.
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