A tetradentate (N2O2) Schiff base (H2Ldfm) was successfully synthesized via condensation of curcumin / diferuloylmethane (dfm) and L-leucine amino acid (HL). There were three different methods that used for synthesizing H2Ldfm; (refluxing, grading, and fusion). Ten different metal complexes were also successfully synthesized by combination of the Schiff base (H2Ldfm) and 1,10-phenanthroline (phen) ligand to form a hexadentate (N4O2) mixed ligands (Ldfm , phen) with ten different metal salts (M) where{ M= Al(III), Mn(II), Fe(III), Co(II), Ni(II), Cu(II), Ag(I), Cd(II), Hg(II), and Pb(II)}. The molar ratio of reactants was (1:1:1) (M: H2Ldfm : phen). The new Schiff base and its new complexes were characterized by different physicochemical tec

Pure grade II titanium disks were coated with a thin coating of polyetherketoneketone (PEKK) polymer by RF magnetron sputtering using either nitrogen or argon gas. Sputtering technique was employed at 50 W for one hour at 60°C with continuous flow of nitrogen or argon gas. Field-emission scanning electron microscopy (FE-SEM) showed a continuous, homogeneous, rough PEKK surface coating without cracks. In addition, cross-sectional FE-SEM revealed an average coat thickness of 1.86 μm with argon gas and 1.96 μm with nitrogen gas. There was homogenous adhesion between the coating layer and substrate. The elemental analysis of titanium substrate revealed the presence of carbon, titanium, and oxygen. The RF magnetron sputtering with argon or ni

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

In this work magnetite/geopolymer composite (MGP) were synthesized using a chemical co-precipitation technique. The synthesized materials were characterized using several techniques such as: “X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), vibrating sample-magnetometer (VSM), field-emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDS), Brunauer–Emmett–Teller (BET) and Barrentt-Joyner-Halenda (BJH)” to determine the structure and morphology of the obtained material. The analysis indicated that metal oxide predominantly appeared at the shape of the spinel structure of magnetite, and that the presence of nano-magnetite had a substantial impact on the surface area and pore st

The major of DDoS attacks use TCP protocol and the TCP SYN flooding attack is the most common one among them. The SYN Cookie mechanism is used to defend against the TCP SYN flooding attack. It is an effective defense, but it has a disadvantage of high calculations and it doesn’t differentiate spoofed packets from legitimate packets. Therefore, filtering the spoofed packet can effectively enhance the SYN Cookie activity. Hop Count Filtering (HCF) is another mechanism used at the server side to filter spoofed packets. This mechanism has a drawback of being not a perfect and final solution in defending against the TCP SYN flooding attack. An enhanced mechanism of Integrating and combining the SYN Cookie with Hop Count Filtering (HCF) mech

With the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to intrusion or misuse and to provide protection to them, so it's important to design powerful and efficient systems-do-this-purpose. It this paper it has been used several varieties of algorithm selection passive immune algorithm selection passive with real values, algorithm selection with passive detectors with a radius fixed, algorithm selection with passive detectors, variable- sized intrusion detection network type misuse where the algorithm generates a set of detectors to distinguish the self-samples. Practica

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

Seeking pharmacist advice about minor ailments is a common practice among Iraqi patients because such advice is free and quick. Unfortunately, the assessment and management of minor ailments by Iraqi pharmacists were inappropriate. Therefore, this study aimed to develop a model for a mobile application that can assist community pharmacists in the diagnosis and management of minor ailments.