In this paper, an intelligent tracking control system of both single- and double-axis Piezoelectric Micropositioner stage is designed using Genetic Algorithms (GAs) method for the optimal Proportional-Integral-Derivative (PID) controller tuning parameters. The (GA)-based PID control design approach is a methodology to tune a (PID) controller in an optimal control sense with respect to specified objective function. By using the (GA)-based PID control approach, the high-performance trajectory tracking responses of the Piezoelectric Micropositioner stage can be obtained. The (GA) code was built and the simulation results were obtained using MATLAB environment. The Piezoelectric Micropositioner simulation model with th

The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A

The investigation of determining solutions for the Diophantine equation  over the Gaussian integer ring for the specific case of  is discussed. The discussion includes various preliminary results later used to build the resolvent theory of the Diophantine equation studied. Our findings show the existence of infinitely many solutions. Since the analytical method used here is based on simple algebraic properties, it can be easily generalized to study the behavior and the conditions for the existence of solutions to other Diophantine equations, allowing a deeper understanding, even when no general solution is known.

An experimental study is conducted on the utilization of the inlet ethanol injection technique in order to evaluate its impact on the performance of a two-shaft T200D mini-gas turbine engine. The maximum degradation recorded in power output was 32.8% at the climate temperature of 45^oC. Nevertheless, at that temperature, adding ethanol with Eth/LPG ratio of 20% by volume brought an enhancement in power output of 19.2% compared to normal LPG run. SFC of the dual-fuel engine ranked a level of 22% higher than that with pure LPG consumption. The overall efficiency suffered a maximum reduction of 14.4% with Eth/LPG fuel ratio of 20%, but when the loading was raised beyond 70% of the engine full load; the efficiency of dual-fuel engi

Background: preparation of root canals is an important step in root canal treatment. Mechanical instrumentation of root canals cause an irregular layer of debris, known as the smear layer. As a result, several studies reported that preferring the removal of the smear layer. Objective: To study the influence of the energy (100 mJ) of Erbium, Chromium: Yttrium Scandium Gallium Garnet (Er,Cr:YSGG) laser at short pulse duration (60 μs)  on smear layer removal of apical third after using Photon induced photoacoustic streaming technique. Materials and methods: Eighteen straight single-rooted mandibular premolars were used. The roots length were uniform to 14mm from the anatomic apex and

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

Roller Compacted Concrete is a type of concrete that is environmentally friendly and more economical than traditional concrete. Roller Compacted Concrete is typically used for heavy-duty and specialist constructions, such as hydraulic structures and pavements, because of its coarse surface. The main difference between RCC and conventional concrete mixtures is that RCC has a more significant proportion of fine aggregates that allow compaction and tight packing. In recent years, it has been estimated that several million tons of waste demolished material (WDM) produced each year are directed to landfills worldwide without being recycled for disposal. This review aimed to study the literature about creating a Roller-Comp

The temperature control process of electric heating furnace (EHF) systems is a quite difficult and changeable task owing to non-linearity, time delay, time-varying parameters, and the harsh environment of the furnace. In this paper, a robust temperature control scheme for an EHF system is developed using an adaptive active disturbance rejection control (AADRC) technique with a continuous sliding-mode based component. First, a comprehensive dynamic model is established by using convection laws, in which the EHF systems can be characterized as an uncertain second order system. Second, an adaptive extended state observer (AESO) is utilized to estimate the states of the EHF system and total disturbances, in which the observer gains are updated