In recent years, the positioning applications of Internet-of-Things (IoT) based systems have grown increasingly popular, and are found to be useful in tracking the daily activities of children, the elderly and vehicle tracking. It can be argued that the data obtained from GPS based systems may contain error, hence taking these factors into account, the proposed method for this study is based on the application of IoT-based positioning and the replacement of using IoT instead of GPS.  This cannot, however, be a reason for not using the GPS, and in order to enhance the reliability, a parallel combination of the modern system and traditional methods simultaneously can be applied. Although GPS signals can only be accessed in open spaces, GP

The adsorption of copper ions onto produced activated carbon from banana peels (with particle size 250 µm) in a single component system with applying magnetic field has been studied using fixed bed adsorber. The fixed bed breakthrough curves for the copper ions were investigated. The adsorption capacity for Cu (II) was investigated. It was found that 1) the exposure distance (E.D) and strength of magnetic field (B), affected the degree of adsorption; and 2) experiments showed that removal of Cu ions and accumulative adsorption capacity of adsorbent increase as the exposure distance and strength of magnetic field increase.
 

This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH₂) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

Four samples were collected from the wastewater of State Battery Manufacturing Company (SBMC); Babylon 2 factory in AL-Waziriya district, as triplicates. Physical and chemical measurements were carried out such as temperature, pH, Lead concentrations and their ranges were: (19.5-34.5) °C, (6.1-6.4) and (4.5-6.5) mg/L, respectively. Six dominant Bacillus spp. isolates were isolated from these samples; namely, Bacillus subtilis N1, Bacillus subtilis N2, Bacillus subtilis N3, Bacillus cereus N4, Bacillus cereus N5 , Bacillus cereus N6. These isolates were capable of removing Lead from aqueous solutions in a capacity reached 27.6 ± 1.4, 10.1 ± 1.7, 74.5 ± 0.7, 8.93 ± 2.8, 8.1 ± 3.5, 1.6± 0.7 mg/L, respectively. Whereas cell walls,

Electro coagulation treatment was used for zinc removal from electroplating wastewater of the State Company for Electrical Industries . This wastewater, here consists zinc ions with maximum concentration in solution of 90 ppm .

The parameters that influenced the wastewater treatment are: current density in the range  1-1.4 mA/cm2, pH  in the range 5-10, temperature in the range 25-45°C and time in the range 10-180 minute.

The research is a laboratory experimental type using batch system for electrical process with direct current. The cell comprised of aluminum electrode as anode and stainless steel electrode as cathode. Thirty experiments and one hundred fifty sample lab tests were carried out in this research

Decision making is vital and important activity in field operations research ,engineering ,administration science and economic science with any industrial or service company or organization because the core of management process as well as improve him performance . The research includes decision making process when the objective function is fraction function and solve models fraction programming by using some fraction programming methods and using goal programming method aid programming ( win QSB )and the results explain the effect use the goal programming method in decision making process when the objective function is
fraction .

In this paper, we deal with games of fuzzy payoffs problem while there is uncertainty in data. We use the trapezoidal membership function to transform the data into fuzzy numbers and utilize the three different ranking function algorithms. Then we compare between these three ranking algorithms by using trapezoidal fuzzy numbers for the decision maker to get the best gains

The development of a reversed phase high performance liquid chromatography fluorescence method for the determination of the mycotoxins fumonisin B1 and fumonisin B2 by using silica-based monolithic column is described. The samples were first extracted using acetonitrile:water (50:50, v/v) and purified by using a C18 solid phase extraction-based clean-up column. Then, pre-column derivatization for the analyte using ortho-phthaldialdehyde in the presence of 2-mercaptoethanol was carried out. The developed method involved optimization of mobile phase composition using methanol and phosphate buffer, injection volume, temperature and flow rate. The liquid chromatographic separation was performed using a reversed phase Chromolith® RP-18e column