This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

Nanofiltration (NF) ceramic membrane have found increasing applications particularly in wastewater and water treatment. In order to estimate and optimize the performance of NF membranes, the membrane should be characterized correctly in terms of their basic parameters such as effective pore radius (r_p) and equivalent effective thickness as well as effective surface charge ( ), the effective charge density ( ) and Donnan potential ( ). The impact of electrokinetic (zeta) potential on the membrane surface charge density, effective membrane charge density and Donnan potential at two different concentrations of the reference solutions 0.001, 0.01 M sodium chloride at various pH values from 3 to 9, and effective po

Quadrotors are coming up as an attractive platform for unmanned aerial vehicle (UAV) research, due to the simplicity of their structure and maintenance, their ability to hover, and their vertical take-off and landing (VTOL) capability. With the vast advancements in small-size sensors, actuators, and processors, researchers are now focusing on developing mini UAV’s to be used in both research and commercial applications. This work presents a detailed mathematical nonlinear dynamic model of the quadrotor which is formulated using the Newton-Euler method. Although the quadrotor is a 6 DOF under-actuated system, the derived rotational subsystem is fully actuated, while the translational subsystem is under-actuated. The der

The aim of human lower limb rehabilitation robot is to regain the ability of motion and to strengthen the weak muscles. This paper proposes the design of a force-position control for a four Degree Of Freedom (4-DOF) lower limb wearable rehabilitation robot. This robot consists of a hip, knee and ankle joints to enable the patient for motion and turn in both directions. The joints are actuated by Pneumatic Muscles Actuators (PMAs). The PMAs have very great potential in medical applications because the similarity to biological muscles. Force-Position control incorporating a Takagi-Sugeno-Kang- three- Proportional-Derivative like Fuzzy Logic (TSK-3-PD) Controllers for position control and three-Proportional (3-P) controllers for force contr

Surfaces quality is one of the most specified customer requirements for machine parts. The major indication of surfaces quality on machined parts is surface roughness. The research aim is to study the cutting conditions and their effects on the surface roughness. This paper utilizes regression models to predict surface roughness over the machining time for variety of cutting conditions in turning. In the experimental part for turning, different types of materials (Aluminum alloy, Copper alloy, and Gray cast iron) were considered with different cutting speed ( ) and feed rate ( ). A mathematical Model depending on statistical-mathematical method between surface roughness (Rz ) and cutting condition ( , ) were derived, for the three materials

The significance of the research lies in the fact that electronic technologies represent an important step in evaluating legal situations, and the research problem centered on the lack of attention to visual requirements and the absence of a clear image of legal situations that may be difficult for the referee to apply correctly in addition to the lack of focus on visual requirements and the unclear depiction of some legal cases which make it difficult for the referee to interpret them correctly This is because the referee's main tool is visual perception, which interprets live situations such as violations, fouls, and other cases that arise during a game Moreover, there are numerous responses and challenges in evaluating legal situ

Dairy wastewater generally contains fats, lactose, whey proteins, and nutrients. Casein precipitation causes the effluent to decompose into a dark, strong-smelling sludge. Fluid waste contains soluble organic matter, suspended solids, and gaseous organic matter, which cause undesirable taste and smell, grant tone and turbidity, and advance eutrophication, which plays an essential role in increasing biological oxygen demand (BOD) in water. It also contains detergents and disinfecting agents from the rinses and washing processes, which increase the need for chemical oxygen (COD). One of the characteristics of dairy effluents is their relatively high temperature, high organic contents, and wide pH range, so the discharge of wastewater into

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n