Recently, Knowledge Management Systems (KMS) consider one of the major fields of study in educational institutions, caused by the necessity to identify their knowledge value and success. Hence, based on the updated DeLone and McLean’s Information Systems Success Model (DMISSM), this study set out to assess the success of the Perceived Usefulness of Knowledge Management Systems (PUKMS) in Iraqi universities. To achieve this objective, the quantitative method is selected as the research design. In total, 421 university administration staff members from 13 Iraqi private universities were conducted. This study highlights a number of significant results depending on structural equation modeling which confirms that system, information, and s

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

In this work Nano crystalline (Cu2S) thin films pure and doped 3% Al with a thickness of 400±20 nm was precipitated by thermic steaming technicality on glass substrate beneath a vacuum of ~ 2 × 10− 6 mbar at R.T to survey the influence of doping and annealing after doping at 573 K for one hour on its structural, electrical and visual properties. Structural properties of these movies are attainment using X-ray variation (XRD) which showed Cu2S phase with polycrystalline in nature and forming hexagonal temple ,with the distinguish trend along the (220) grade, varying crystallites size from (42.1-62.06) nm after doping and annealing. AFM investigations of these films show that increase average grain size from 105.05 nm to 146.54 nm

This research aims to improve the radiation shielding properties of polymer-based materials by mixing PVC with locally available building materials. Specifically, two key parameters of fast neutron attenuation (removal cross-section and half-value layer) were studied for composite materials comprising PVC reinforced with common building materials (cement, sand, gypsum and marble) in different proportions (10%, 30% and 50% by weight). To assess their effectiveness as protection against fast neutrons, the macroscopic neutron cross-section was calculated for each composite. Results show that neutron cross-section values are significantly affected by the reinforcement ratios, and that the composite material PVC + 50% gypsum is an effect