Determining the optimum product mix under the theory of constraints (TOC) has been considered by many researchers. In most cases, researches consider one scenario with one important aspect which is maximizing the profit by giving the best solution. This paper solves a product mix problem faced by a birds' food production facility. The problem is modeled and solved using two linear programing models. Several scenarios are presented for the same problem considering two important aspects, namely, resources' utilization and productivity. Data visualization is extensively used in this paper to

Trajectory tracking of unmanned aerial vehicles (UAVs) has been studied nowadays because it is necessary to design new controllers under different conditions. Severe atmospheric conditions are one of the major problems to overcome according to the path of the UAV. Conditions such as wind speed that can vary according to the weather conditions can affect the flight performance and of course in extreme cases can lead to stability problems. Some kinds of severe conditions are storms, snow, and hurricanes. These conditions are considered as disturbances in the roll, pitch, and yaw orientations of

Despite significant efforts to democratize artificial intelligence (AI), computer vision which is a sub-field of AI, still lags in Africa. A significant factor to this, is the limited access to computing resources, datasets, and collaborations. As a result, Africa's contribution to top-tier publications in this field has only been 0.06% over the past decade. Towards improving the computer vision field and making it more accessible and inclusive, this study analyzes 63,000 Scopus-indexed computer vision publications from Africa. We utilize large language models to automatically parse their

A fault detection algorithm is proposed in this paper for wind farms. The algorithm is based on machine learning adopting Support Vector Machines (SVM). The focus is on the detection of grid faults for a Wind Farm of Doubly Fed Induction Generator (WF-DFIG). A high-fidelity model is used to simulate the system performance in faulty and healthy conditions. Statistical features based on steady-state signal analysis of measured signals are extracted. Machine learning results on a 9MW model WF-DFIG Grid-connected are provided by MATLAB/SIMULINK. The model performance is clarified and success in

This study aims to increase the effectiveness of photovoltaic pumping systems. A practical installation and cost-effective design are suggested. This paper examines the nonlinear behaviour of photovoltaic generators from a distinct perspective; where it repeatedly transitions between a constant current and a constant voltage source and shows how this affects the behaviour of the induction motors. A Fractional-order Neural Network (FONN) is suggested to forecast the harvested solar-energy. The results showed that FONN improved forecasting accuracy by effectively capturing the nonlinear

This research paper investigates the optimal control of the ball and beam system, a challenging fourth-degree system that is commonly used in control studies. Four different control techniques, namely cascaded PD-P, cascaded PD-PD, optimized cascaded PD-PD control using a genetic algorithm, and state feedback control, are compared in terms of their performance. The study aims to achieve specific design criteria, including low rise time, less than three percent overshoot, and less than two seconds of settling time. In addition, the impact of disturbances, uncertainty, control action, and beam

This paper aims to implement an efficient model of the most optimum path to follow an object on a Self Driving Vehicle (SDV). The path of the vehicle is predicted by using Machine Vision (MV) and Neural networks (NN) model. The NN model uses numerous amounts of training data. First the system works by using the MV algorithms to detect objects with predefined colors. Then, the location of the object is fed to the trained NN to get the speeds of the motors needed to reach the object. The training data are obtained from the manual driving of the vehicle in different experiment settings. In this

This paper introduces the concept of thermal air braking, which involves heating a portion of the airfoil's upper surface to achieve the braking effect. A 2D Computational Fluid Dynamics (CFD) analysis is conducted using ANSYS Fluent software to study the impact of heating the upper back portion of the top surface of an airfoil. The study compares the results of the heated and non-heated cases for NACA 4415. Different aerodynamic efficiencies are investigated, such as lift coefficient (CL), drag coefficient (CD), lift-to-drag coefficient (CL/CD), and pressure coefficient (CP). The results are

The field of rehabilitation robotics for upper limb assistance has grown rapidly in the past few years. Rehabilitation robots have direct contact with human joints, which presents a serious safety concern. In this paper, a novel design for a series elastic actuator (SEA) is presented for upper limb rehabilitation of sensorimotor dysfunctions. The proposed SEA ensures safety and robust torque control under various disturbances. The proposed SEA is modeled and simulated using MATLAB Simulink to obtain Input/Output driven data. For the proposed system, two modeling approaches, ARMAX and NN, are

Impairments in the sensorimotor system negatively impact the ability of individuals to perform daily activities autonomously. Upper limb rehabilitation for stroke survivors and cerebral palsy (CP) children is essential to enhance independence and quality of life. Robot assisted therapy has been a bright solution in the last two decades to promote the recovery process for neurological disorders patients. Nevertheless, defining the optimum intervention of robot assisted therapy (RAT) in different cases is not clear yet. With this aim, the presented study reviewed the current literature on RAT