The important of present study is to design rehabilitation program by using hypermedia for some injuries of smooth tissues in shoulder joint.   This joint is most important to help badminton players in achieving their daily and sport tasks due to upper limp movements depend on health and active of this joint. Experimental approach with a manner of equal single station was used in present study and study simple consisted of 6 badminton players from Babylon and Al-Mahaweel clubs who have less sharp tissue smooth injury such (muscles, ligaments, pocket). We used (SPSS) to analyses pre, medal, post-tests data. In conclusion, hypermedia is positive benefit to rehabilitee of injuries of smooth tissues in shoulder joint for badminton pla

The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T

     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

In this study, the induced splined shaft teeth contact and bending stresses have been investigated numerically using finite element method(Ansys package version 11.0) with changing the most effecting design parameter,(pressure angle, teeth number, fillet radius and normal module), for internal and external splined shaft. Experimental work has been achieved using two dimensional photoelastic techniques to get the contact and bending stresses; the used material is Bakelite sheet type “PSM-4”.
The results of numerical stress analysis indicate that, the increasing of the pressure angle and fillet radius decrease the bending stress and increase the contact stress for both internal and external spline shaft teeth while the increasing of

A novel concept of air heater using a heating element made from Aluminum metal porous disc surrounded by a DC resistive electrical heater inserted in the mid-plane of a copper tube of (52.8 mm) diameter and (480 mm) length is presented herein. Study of the developed heater is conducted; using different porous disc thicknesses of (20, 40, 60 mm), heater wall temperatures (106 °C and 119 °C), and flow rates rare varied from (100–300 L/min). Al-metal foam disc has been made using the metal powder technology. Different resistive electrical heaters according to the type of porous disc used have been manufactured. A 2-D computational model is developed, using continuity, momentum, and energy equations for turbulent forced flow in plain tube,

The general health of palm trees, encompassing the roots, stems, and leaves, significantly impacts palm oil production, therefore, meticulous attention is needed to achieve optimal yield. One of the challenges encountered in sustaining productive crops is the prevalence of pests and diseases afflicting oil palm plants. These diseases can detrimentally influence growth and development, leading to decreased productivity. Oil palm productivity is closely related to the conditions of its leaves, which play a vital role in photosynthesis. This research employed a comprehensive dataset of 1,230 images, consisting of 410 showing leaves, another 410 depicting bagworm infestations, and an additional 410 displaying caterpillar infestations. Furthe

In the present study, the growth and total lipid contents of two oleaginous fungal isolates Aspergillus terreus, Aspergillus fumigatus were compared in different nitrogen and organic carbon sources.  Artificially the fungi were cultured on media consisting of various mono- or di- or polysaccharides and  peptone or yeast extract as elementary sources for carbon and nitrogen, respectively. Media containing sucrose /yeast extract or glucose/ yeast extract were the most effective for lipid production from fungal, during  two weeks  incubation period, the highest biomass of dry weight was (19.6 , 18.8) g / L , (25.8 , 30.5) g /L  and  lipid yield (1, 0.97 )g/L, (0.65, 0.65) g/ L for two isolates Aspergillus terreus

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re