The current research includes a look at the participation of Iraqi women in the combat roles, which starts from the assumption of the democratic transition that must be led - in one of its aspect - until the army or the military foundation to become a "citizen army," the matter which is represented a demand increasingly needed in the experiences of Democratic transformation that facing serious security challenges such as in Iraq, this means that the army or security foundation - which is involved in counterterrorism - should not reflect a specific group in society , and hence embody the most important democratic principles, which are equality and equal opportunities, especially gender equality. On the other hand, the influence of armed conf

Biodiesel production from microalgae depends on the biomass and lipid production. Both biomass and lipid accumulation is controlled by several factors. The effect of various culture media (BG11, BBM, and Urea), nutrients stress [nitrogen (N), phosphorous (P), magnesium (Mg) and carbonate (CO₃)] and gamma (γ) radiation on the growth and lipid accumulation of   Dictyochloropsis splendida were investigated. The highest biomass and lipid yield of D. splendida were achieved on BG11 medium. Cultivation of D. splendida in a medium containing 3000 mg L⁻¹ N, or 160 mg L⁻¹ P, or 113 mg L⁻¹ Mg, or 20 mg L^-1 CO_3, led to enhanced growth rate. While u

The current research aims to first - reveal the social repercussions of COVID-19 on women A - The impact of the epidemiological crisis on the social structure of the family B - Psychological and social pressures that women are exposed to during the Covid pandemic C - Social isolation resulting from the injury of a member Second - Understanding the health consequences of COVID-19 on women A- Mechanisms of differentiation in the treatment of Covid-19 treatment, home or hospital As for the limits of the research, the current research is determined by some private universities of students, female employees and teaching staff in Karkh district, which number eight (Al-Hikma, Al-Farahidi, Al-Farabi, Tigris, AlTurath, Al-Rashid, Al-Mashreq, Al-Nuso

This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota

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