A new Schiff base ligand was prepared via a condensation reaction. The synthesis involved combining N-(4-aminophenylsulfonyl) benzamide (also known as sulfabenzamide) with indoline-2,3-dione. To facilitate the reaction, three drops of glacial acetic acid were added. This process yielded the ligand N-(4-(2-oxoindoline-3-ylideneamino) phenylsulfonyl) benzamide, designated as (L). Mixed ligand complexes were prepared in a molar ratio (1:1:1) (M:1,10-phen, L) at concentrations of 10-4M by interacting L and 1,10-phenanthroline, with the following metal ions (Cr+3, Mn+2, Zn+2, Pd+2, Cd+2, Pt+4). These complexes exhibited different geometric shapes, including (octahedral for both Cr+3, Mn+2, Pt+4, tetrahedral for Zn+2 and Cd+2, an

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi

This work is based on the synthesis of Cobalt(II) and Cadmium(II) mixed-ligands compounds obtained from the reaction of N'-(4-methylsulfanyl-benzoyl)-hydrazine carbodithioic acid methyl ester as a ligand and using ethylendiamine (en), 2,2'-bipyridine (bipy) or 1,10-phenanthroline (phen) as a co-ligand. The synthesis of ligand (HL) was based on multi-steps synthetic procedure. The reaction of 4-methylsulfanyl-benzoyl chloride with hydrazine gave 4-methylsulfanyl-benzoic acid hydrazide. This compound was reacted with carbon disulfide and potassium hydroxide in methanol to yield N'-(4-methylsulfanylbenzoyl)-hydrazine potassium thiocarbamate, which upon reaction with methyl iodide resulted in the formation of the ligand. A range of physico-chem

Microbial activity of Ellagic acid when mixed with some types of candy toward Streptococcus mutans microorganism was studied. The main purpose of carrying out this study is to produce a new type of candy that contains Ellagic acid in addition to xylitol instead of sucrose to prevent dental caries. The results show that the inhibitory action of Ellagic acid was more effective when mixed with this type of candy for the purpose of reducing Streptococcus mutans microorganisms, while sensory evaluation was applied in this study to 20 volunteers to that candy sample evaluated which contain (5 mg/ml) Ellagic acid with 100g xylitol to determine consumers acceptability of this sample of candy. The results were expressed as mean value, slandered d

This study was conducted to determine the ability of water treatment system (Vortisand) to reduce some chemical and physical properties for tigris river raw water, It consisted of turbidity, electrical conductivity, pH, total hardness, calcium Hardness as well as temperature in order to determine the unit`s efficiency for reducing their concentration as compared to those in the water produced by some classical potable water projects (Dora and Wathba) in Baghdad. Samples were collected during the cold months (December 2016 and January 2017) and during the hot months (May and June 2017). The results showed that this system has the ability to reduce some properties such as turbidity, the values were 215NTU in raw water and decreased to NTU

Vehicular ad hoc networks (VANETs) are considered an emerging technology in the industrial and educational fields. This technology is essential in the deployment of the intelligent transportation system, which is targeted to improve safety and efficiency of traffic. The implementation of VANETs can be effectively executed by transmitting data among vehicles with the use of multiple hops. However, the intrinsic characteristics of VANETs, such as its dynamic network topology and intermittent connectivity, limit data delivery. One particular challenge of this network is the possibility that the contributing node may only remain in the network for a limited time. Hence, to prevent data loss from that node, the information must reach the destina

This work presents the use of laser diode in the fiber distributed data interface FDDI networks. FDDI uses optical fiber as a transmission media. This solves the problems resulted from the EMI, and noise. In addition it increases the security of transmission. A network with a ring topology consists of three computers was designed and implemented. The timed token protocol was used to achieve and control the process of communication over the ring. Nonreturn to zero inversion (NRZI) modulation was carried out as a part of the physical (PHY) sublayer. The optical system consists of a laser diode with wavelength of 820 nm and 2.5 mW maximum output power as a source, optical fiber as a channel, and positive intrinsic negative (PIN) photodiode

It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in