In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

Due to the need for controlling and regulating of feed pellet. Pellet that is imported or locally manufactured is accompanied by cracking and crumbling percentage that occur during transporting and distributing to animals, using conveyors and mechanical feeders. This study aimed to determine the effect of particle size and die holes diameter in the machine on broiler feed pellets quality in pellet durability, pellet direct measurement, pellet expansion, and pellet length. Three particle size 2, 4, and 6 mm, and three diameters of die holes in the machine 3, 4, and 5 mm, have been used. The results showed that changing the particle size from 2 to 4 then to 6 mm led to a significant decrease in pellet durability and pellet lengths, pe

Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil

This is a survey study that presents recent researches concerning factional controllers. It presents several types of fractional order controllers, which are extensions to their integer order counterparts. The fractional order PID controller has a dominant importance, so thirty-one paper are presented for this controller. The remaining types of controllers are presented according to the number of papers that handle them; they are fractional order sliding mode controller (nine papers), fuzzy fractional order sliding mode controller (five papers), fractional order lag-lead compensator (three papers), fractional order state feedback controller (three papers), fractional order fuzzy logic controller (three papers). Finally, several conclusions

Radiation measuring devices need to process calibration which
lose their sensitivity and the extent of the response and the amount of
stability under a changing conditions from time to time and this
period depends on the nature and use of field in which used devices.
A comparison study was done to a (451P) (ionization chamber
survey meter) and this showed the variation of calibration factor in
five different years. This study also displayed the concept of
radiation instrument calibration and necessity of every year
calibration of them.
In this project we used the five years calibration data for ionization
chamber survey meter model Inspector (451P) to get that the values
of Calibration Factor (CF) and Res

This is a survey study that presents recent researches concerning factional controllers. It presents several types of fractional order controllers, which are extensions to their integer order counterparts. The fractional order PID controller has a dominant importance, so thirty-one paper are presented for this controller. The remaining types of controllers are presented according to the number of papers that handle them; they are fractional order sliding mode controller (nine papers), fuzzy fractional order sliding mode controller (five papers), fractional order lag-lead compensator (three papers), fractional order state feedback controller (three papers), fractional order fuzzy logic controller (three papers). Finally,

This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi