Sesame crop, one of the very important oily, industrial, and summer crops that is economically important, has been investigated. The plantation and production of this crop has been studied in Al-Qadisiyah governorate during 2003-218. This is because this governorate is well-known by sesame plantation. Such a study helps to know the geographical distribution of sesame agricultural season in 2017-2018, and explore the most important natural factors that affect its plantation. Different research approaches have been adopted based on that facts that need to be met. A field study approach has been used in studying sesame crop descriptively and conceptually, shedding light on its nutritional and economic importance. Moreover, a descriptive com

The objective of this research is to identify the effect of Using Fryer strategy on achievement and systemic thinking in the subject of chemistry of second class intermediate school students. The sample of research consisted of 59 students in one intermediate school in Baghdad/Iraq, split into two groups; experimental and control. The scientific material of the study is related to Chapters II and III of the Science Book for the second Intermediate School for the Year (2019-2020). The scientific test is composed of 25 test items whilst the second instrument for research related to systematic thinking test consisted of 12 items. The results of the research showed that the use of Fryer's chemistry-teaching strategy has increased achieve

Alopecia areata is a common disorder, hypothesized to be autoimmune in etiology. Cortisone taken orally may stimulate new hair growth. Prednisone (orally administered steroid (has proved effective for patients with alopecia areata, but its potential side effects include weight gain, metabolic abnormalities, acne and menstrual problems.

This clinical study was designed to assess the clinical significance of the nutrient antioxidants (vitamin A, vitamin E and vitamin C) in reducing the dose of corticosteroids (prednisolone), and as a consequence, their side effects in patient with alopecia. The results of this study reveal the potential clinical significance of the therapy for two months with these antioxidants in reducing the dose

Receipt date:6/3/2021  acceptance date:4/5/2021 Publication date:31/31/2021

This work is licensed under a Creative Commons Attribution 4.0 International License.

The research in the role of variables contact for non-state actors have become more influential in the current of contemporary events, that related with the reality of seeking services and providing all of that in favor of maintaining the social peace, and ensuring its empowerment in order to make peace and stability outcomes as a real fa

The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

Extracorporeal Shock Wave Lithotripsy (ESWL) is the most commonplace remedy for kidney stone. Shock waves from outside the body frame are centered at a kidney stone inflicting the stone to fragment. The success of the (ESWL) treatment is based on some variables such as age, sex, stone quantity stone period and so on. Thus, the prediction the success of remedy by this method is so important for professionals to make a decision to continue using (ESWL) or tousing another remedy technique. In this study, a prediction system for (ESWL) treatment by used three techniques of mixing classifiers, which is Product Rule (PR), Neural Network (NN) and the proposed classifier called Nested Combined Classi

     Staphylococcus haemolyticus is one of the most frequently isolated coagulase-negative staphylococci. The ability to form biofilm is considered as one of the most important virulence factors of coagulase negative staphylococci. There is only limited knowledge of the nature of S. haemolyticus biofilms. This study was aimed at evaluating the ability of S. haemolyticus strains to produce biofilm in the presence of copper oxide nanoparticles (CuONPs). The biological synthesis of nanoparticles is an environmentally friendly approach for large-scale production of nanoparticles. Copper oxide nanoparticles were produced in the current study from the S. haemolyticus viable cell filtrate. UV-visible (UV-Vis) spectroscopy, X-ray diffra

     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