Modern automation robotics have replaced many human workers in industrial factories around the globe. The robotic arms are used for several manufacturing applications, and their responses required optimal control. In this paper, a robust approach of optimal position control for a DC motor in the robotic arm system is proposed. The general component of the automation system is first introduced. The mathematical model and the corresponding transfer functions of a DC motor in the robotic arm system are presented.  The investigations of using DC motor in the robotic arm system without controller lead to poor system performance. Therefore, the analysis and design of a Proportional plus Integration plus Divertive (PID) controller is illustrated.

Soil salinization is a pervasive global issue, particularly in semi-arid and dry areas. It constitutes the primary cause of soil degradation, significantly impairing soil functionality and agricultural productivity. Consequently, there is a pressing need for precise procedures to measure soil salinity in various areas, which are necessary for managing, correcting, monitoring, and utilizing saline soils effectively. This study employed remote sensing (RS) techniques as a robust approach for constructing predictive models of soil salinity by examining changes in soil salinity using different salinity indices and comparing them with electrical conductivity (EC) measurements for soil samples. Among the five salinity indices evaluated, t

Citrus diseases are the main issue for agricultural productivity, which cause a reduction in yield and quality, thus causing economic loss; also, we see that traditional methods of diagnosis, which are very subjective and prone to error, and thus we need to suggest accurate automated detection systems. In this study, we present a hybrid model that integrates conventional machine learning with deep learning models. We used the Gray Level Co-occurrence Matrix (GLCM) for feature extraction, which is classified via machine learning algorithms like k-Nearest Neighbors (KNN), Decision Tree (DT), Linear Discriminant Analysis (LDA), and Random Forest (RF). At the same time, deep convolutional neural networks (DCNNs), GoogLeNet, and ResNet18

COVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduce