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

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

The fouling depositions of crude oil stream were studied theoretically in a shell and tube heat exchanger to investigate the effect of depositions on the heat transfer process. The employed heat exchanger was with steam flowing in the inner tubes and crude oil in the shell at different velocities and bulk temperatures. It is assumed that fouling occurs only on the heated stream side (crude oil). The analysis was carried out for turbulent flow heat transfer conditions with wide range of Reynolds number, bulk temperature and time. Many previously proposed models for fouling resistance were employed to estimate a new model for fouling rate. It is found that the fouling rate and consequently the heat transfer coefficient were affected by Rey

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

In this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate k_p (10^-12g².cm^-4.s^-1) in Incoloy 800H at 900^oC . ANN was used for estimating the predicted values of hot corrosion rate k_p (10^-12g².cm^-4.s^-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic alg