Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

SnS nanobelt thin films were deposited on glass substrates in acidic solution by chemical bath deposition (CBD) method. The belt-like morphologies of as-deposited SnS thin films were characterized by scanning electron microscope (SEM) and transmission electron microscopy (TEM). X-ray diffraction (XRD) and Raman measurements were carried out to confirm the crystal structures and phase purities of SnS nanobelt thin films. The morphologies and phase purities of SnS thin films were influenced greatly by the tin and sulfur precursors. The bandgaps of SnS nanobelts were determined to be 1.39–1.41 eV by UV–vis absorption and photoluminescence (PL) spectra. Current-voltage ((I-V)) and current-time ((I-T)) characteristics were studied to demon

Zerumbone (ZER), a natural compound has been extracted from Zingiber zerumbet with known pharmacological activities. The aim was to determine the anti-human Burkitt’s lymphoma (Raji) cell effect of ZER. The 3-(4,5-dimethylthiazol-2-yl)-2,5,-diphenyltetrazolium bromide (MTT) assay was used to determine cytotoxic effect while the Annexin-V-fluorescein isothiocyanate/propidium iodide-PI flow cytometric assays was used to determine apoptotic effect of ZER on the human Burkitt’s lymphoma (Raji) cell (ATCC CCL-86) cell line. The expressions of Bax, Bcl-2, and c-Myc genes were determined via real-time PCR. ZER suppressed the proliferation of Raji cells with a 48 h IC50 value of 5.1 μg/mL. Treated Raji cells also underwen

The aim of the present research is to investigate the effecting of pH parameter on the feasibility of lead removal from simulated wastewater using an electrochemical system. Electrocoagulation method is one of electrochemical technology which is used widely to treat industrial wastewater. Parameters affecting this operation, such as initial metal concentration, applied current, stirrer speed, and contact time of electroprocessing were taken as 155ppm, 1.5 Ampere, 150 rpm, 60 minutes respectively. While pH of the simulated wastewater was in the range of  2 to 12 in the experiments. It was found from the results that pH is an important parameter affecting lead removal operation. The best value of pH parameter is appro

Cystic fibrosis (CF) is an autosomal recessive multisystem disease that results from mutation(s) of the cystic fibrosis transmembrane conductance regulator (CFTR) gene. More than 2100 mutations and polymorphisms have been reported in this gene so far. Incidence and genotyping of CF are under-identified in Iraq. This study aims to determine the types and frequencies of certain CFTR mutations among a sample of Iraqi CF patients. Two groups of patients were included: 31 clinically confirmed CF patients in addition to 47 clinically suspected patients of CF. All confirmed pa

This study aims to evaluate the performance of the sewage treatment plant in Al-Diwaniya, one of cities in the southern part in Iraq. This evaluation could be used to facilitate effluent quality assessment or optimal process control of the plant. The influent reaching the plant is considered a medium to strong in strength with BOD5/COD ratio in the range 0.23 and 0.69 which can be considered an easily degradable sewage by the biological processes performed by the activated sludge unit. The quality of the effluent was found to be higher than the Iraqi standards for disposal to water bodies. The BOD5/COD ratios of the treated sewage varied over a wide range as low of 0.13 to 1.48 indicating operational problems in the plant. Regression ana