Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

Background: The posterior slope of the articular eminence of completely edentulous patients compared to patients with maintained occlusion shows significant flattening. This study aimed to correlate between the flattening of the posterior slope of the articular eminence, with dental status, age, genders, on both sides using computed tomography. Materials and Methods: The sample of the present study was a total of 117 Iraqi subjects, who admitted to the maxillofacial department at Al-Sadr Teaching Hospital in Al-Najaf city. The examination was performed on CT scanner; the eminence inclination was measured in two methods using sagittal section. Results: Clinically, the inclination of articular eminence was higher in edentulous subjects than i

The involvement of maxillofacial tissues in SARS‐CoV‐2 infections ranges from mild dysgeusia to life‐threatening tissue necrosis, as seen in SARS‐CoV‐2‐associated mucormycosis. Angiotensin‐converting enzyme 2 (ACE2) which functions as a receptor for SARS‐CoV‐2 was reported in the epithelial surfaces of the oral and nasal cavities; however, a complete understanding of the expression patterns in deep oral and maxillofacial tissues is still lacking.

Semi-active suspension systems have emerged as an attractive alternative to fully active suspensions because they offer a superior capacity to improve vehicle ride comfort and handling performance with significantly lower energy consumption. Conventional semi-active control strategies, however, such as skyhook damping, often cannot accommodate the nonlinear and time-varying dynamics of vehicles in operation under impulse or severe road disturbances. In this context, an intelligent smart-damper controller is proposed in this paper by incorporating a Modified Fuzzy Adaptive Fuzzy Logic Control framework in a half-car suspension model. In the developed controller, the effective damping force is adaptively tuned using real-time measurements of

sensor sampling rate (SSR) may be an effective and crucial field in networked control systems.  Changing sensor sampling period after designing the networked control system is a critical matter for the stability of the system. In this article, a wireless networked control system with multi-rate sensor sampling is proposed to control the temperature of a multi-zone greenhouse. Here, a behavior based Mamdany fuzzy system is used in three approaches, first is to design the fuzzy temperature controller, second is to design a fuzzy gain selector and third is to design a fuzzy error handler. The main approach of the control system design is to control the input gain of the fuzzy temperature controller depending on the cur

This study is conducted to determine the effect of pathogenicity of the fungus Lecanicillium lecanii in some aspects of life of the insect saw toothed beetle Oryzaephilus surinamensis L. (Coleoptera: Silvanidae) under laboratory conditions with three concentrations of spores and mildew commentator (1 × 103, 1 × 105, 1 × 107) spore / ml , on eggs and larvae second phase of the insect .The study also includs the effect of the fungus concentrations of germination on rice (jasmine) by using direct spray treatment. The results show great fungus efficiency in the control of some aspects of life of the insect, where varied efficiency depends on the concentration of spores, The highest percentage loss of eggs is 63.33% at a concentration

This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used

This paper describes DC motor speed control based on optimal Linear Quadratic Regulator (LQR) technique. Controller's objective is to maintain the speed of rotation of the motor shaft with a particular step response.The controller is modeled in MATLAB environment, the simulation results show that the proposed controller gives better performance and less settling time when compared with the traditional PID controller.