In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

 Finding a path solution in a dynamic environment represents a challenge for the robotics researchers, furthermore, it is the main issue for autonomous robots and manipulators since nowadays the world is looking forward to this challenge. The collision free path for robot in an environment with moving obstacles such as different objects, humans, animals or other robots is considered as an actual problem that needs to be solved.  In addition, the local minima and sharp edges are the most common problems in all path planning algorithms. The main objective of this work is to overcome these problems by demonstrating the robot path planning and obstacle avoidance using D star (D*) algorithm based on Particle Swarm Optimization (PSO)

Abstract

This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is m

In this research tri metal oxides were fabricated by simple chemical spray pyrolysis technique from (Sn(NO₃)₂.20 H₂O, Zn(NO₃)₂.6 H₂O, Cd(NO₃)₂.4 H₂O) salts at concentration 0.1M with mixing weight ratio 50:50 were fabricated on silicon substrate n-type (111). (with & without the presence of grooves by the following diemensions (20μm width, 7.5μm depth) with thickness was about ( 0.1 ±0.05 µm) using water soluble as precursors at a substrate temperature 550 ºC±5, with spray distance (15 cm) and their gas sensing properties toward H₂S gas at different concentrations (10,50,100,500 ppmv) in air were investigated at room te

The Topography, Physical and Optical properties of as-deposited copper oxide CuO absorption layer sprayed using homemade fully computerized CNC spray pyrolysis deposition technique at different deposition speed are reported. These layers are characterized by UV-Visible spectrophotometer, optical microscope, and thickness monitor studies. The optical transmittance study indicates that these layer exhibit high absorption coefficient in the visible range. The optical band gap is found to be at about at speeds (3,6 mm/s). Better homogeneity in CuO layer is found at the speed 5 mm/s. The film thickness lies within the 129-412 nm range.

In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

In earthquake engineering problems, uncertainty exists not only in the seismic excitations but also in the structure's parameters. This study investigates the influence of structural geometry, elastic modulus, mass density, and section dimension uncertainty on the stochastic earthquake response of a multi-story moment resisting frame subjected to random ground motion. The North-south component of the Ali Gharbi earthquake in 2012, Iraq, is selected as ground excitation. Using the power spectral density function (PSD), the two-dimensional finite element model of the moment resisting frame's base motion is modified to account for random ground motion. The probabilistic study of the moment resisting frame structure using stochastic fin

A linear engine generator with a compact double-acting free piston mechanism allows for full integration of the combustion engine and generator, which provides an alternative chemical-to-electrical energy converter with a higher volumetric power density for the electrification of automobiles, trains, and ships. This paper aims to analyse the performance of the integrated engine with alternative permanent magnet linear tubular electrical machine topologies using a coupled dynamic model in Siemens Simcenter software. Two types of alternative generator configurations are compared, namely long translator-short stator and short translator-long stator linear machines. The dynamic models of the linear engine and linear generator, validated

Maintaining and breeding fish in a pond are a crucial task for a large fish breeder. The main issues for fish breeders are pond management such as the production of food for fishes and to maintain the pond water quality. The dynamic or technological system for breeders has been invented and becomes important to get maximum profit return for aquaponic breeders in maintaining fishes. This research presents a developed prototype of a dynamic fish feeder based on fish existence. The dynamic fish feeder is programmed to feed where sensors detected the fish's existence. A microcontroller board NodeMCU ESP8266 is programmed for the developed h

This research aims to understand complexity management and its impact on the use of the dynamic capabilities of a sample of private colleges.  Private colleges are currently facing many crises, changes, unrest and high competitive pressures.  Which is sometimes difficult or even impossible to predict.  The recruitment of dynamic capabilities is also one of the challenges facing senior management at private colleges to help them survive and survive.  Thus, the problem of research was (there is a clear insufficiency of interest in Complexity Management and trying to employ it in improving the dynamic capabilities of Colleges that have been discussed?). A group of private colleges was selected as a