Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

Rehabilitation robots are widely recognized as vital for restoring motor function in patients with lower-limb impairments. A Modified Fractional-Order Proportional-Integral-Derivative (MFOPID) controller is proposed to improve trajectory tracking of a 2-DoF Lower Limb Rehabilitation Exoskeleton Robot (LLRER). The classical FOPID is augmented with a modified control formulation by which steady-state error is reduced and the transient response is sharpened. Controller gains and fractional orders were tuned offline using a hybrid metaheuristic Improved Elk Herd Optimization hybridized with Grey Wolf and Multi-Verse Optimization algorithms (IElk-GM) so that exploration and exploitation are balanced. Superiority over the classical FOPID

The research amid to find out the extent of Iraqi oil companies commitment to implement internal control procedures in accordance with the updated COSO framework. As the research problem was represented in the fact that many of the internal control procedures applied in the Iraqi oil companies are incompatible with most modern international frameworks for internal control, including the integrated COSO framework, issued by the Committee of Sponsoring Organizations of the Tradeway Committee. The research followed the quantitative approach to handling and analysing data by designing a checklist to represent the research tool for collecting data. The study population was represented in the Iraqi oil companies, while the study sample

Periodontitis is a multifactorial chronic inflammatory disease that affects tooth-supporting soft/hard tissues of the dentition. The dental plaque biofilm is considered as a primary etiological factor in susceptible patients; however, other factors contribute to progression, such as diabetes and smoking. Current management utilizes mechanical biofilm removal as the gold standard of treatment. Antibacterial agents might be indicated in certain conditions as an adjunct to this mechanical approach. However, in view of the growing concern about bacterial resistance, alternative approaches have been investigated. Currently, a range of antimicrobial agents and protocols have been used in clinical management, but these remain largely non-v

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

In this study, the electro-hydraulic servo system for speed control of fixed displacement hydraulic motor using proportional valve and (PID) controller is investigated theoretically ,experimentally and simulation . The theoretical part includes the derivation of the nonlinear mathematical model equation of (valve – motor ) combination system and the derivation of the transfer function for the complete hydraulic system , the stability test of the system during the operation through the transfer function using MATLAB package
V7.1 have been done. An experimental part includes design and built hydraulic test rig and simple PID controller .The best PID gains have been calculated experimentally and simulation, speed control performance te

The efficient exploitation of production inventory systems is of significant importance in the modern industrial reality. This paper explores the effect of such a system on dynamic behaviour of a system when the control is provided synergistically by a method called synergetic control (SC). The mathematical model of the system is first constructed and SC introduced to improve the responsiveness of the system when the time-varying demand condition is taken into account. To cope with the problem of unavailability of the systems' state signals and to estimate the demand, the extended state observer (ESO) is introduced. Moreover, mountain gazelle optimizer (MGO) is employed to tune the adjustable design parameters of the SC and the ESO based on