During 2019-2020, the experiment was conducted in the laboratory of the Department of Field Crop Sciences, Faculty of Agricultural Engineering Sciences - Baghdad University, to investigate the impact of soaking wheat seeds produced during the 2016 agricultural season with three plant extracts (licorice root extract 2%, 4% and 6%, Acadian and Humic(500, 1000, & 1500 mg L-1). Aside from the two control treatments (soaking in distilled water with dried seeds). The results show that the soaking treatment with licorice root extract outperformed the other therapies in conventional laboratory germination, root length, and seedling vigor index (95 percent and 3.42 cm 1207) compared to the two control treatments (soaking with distilled w

A field experiment was conducted during the spring season 2020 in Karbala proving/ Al-Sharia Distrit, located at latitude N 32° 42' 13.8" and longitude E 43° 54' 36.6" and at an altitude of 27 m above sea level. The experiment included a study of two factors: the first, Irrigation Interval, three treatments were used: irrigation treatment every 2 days, Irrigation treatment every 4 days, and Irrigation treatment every 6 days. The second factor is the addition of soil conditioners, in which four treatments were used: the control treatment without any addition, the treatment of adding bio-organic fertilizers, the treatment of adding water-conserving technology (polymer), and the treatment of adding water-conserving technology + fertilizers O

This work is concerned with designing two types of controllers, a PID and a Fuzzy PID, to be used
for flying and stabilizing a quadcopter. The designed controllers have been tuned, tested, and
compared using two performance indices which are the Integral Square Error (ISE) and the Integral
Absolute Error (IAE), and also some response characteristics like the rise time, overshoot, settling
time, and the steady state error. To try and test the controllers, a quadcopter mathematical model has
been developed. The model concentrated on the rotational dynamics of the quadcopter, i.e. the roll,
pitch, and yaw variables. The work has been simulated with “MATLAB”. To make testing the
simulated model and the controllers m

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

Abstract 20 patients with osteoarthritis of the knee joint were treated by electrical stimulation in the form of 6 sessions every other day each sessions of diphase fixe (DF) for 4 minutes followed by rest for 4 minutes then treated with a monophase fixe (MF) for 2 minutes. By clinical & statistical analysis ( P value < 0.05) we conclude that the electrical stimulation is effective as one method in the treatment of osteoarthritis.

    This study included isolation and identification of the fungi associated with Aloe vera (L.) in nurseries and plant gardens. The results showed that the fungi Alternaria alternata, Fusarium oxysporum, Fusarium solani, Nigrospora oryzae, Cladosporium herbarum, Stemphylium botryosum, Aspergillus niger, Penicillium sp. were isolated from the diseased leaves of Aloe vera showing spots and blight symptoms. The percentages of disease incidence in March, Jun and August were found to be 5, 50 and 60 %, respectively. Pathogenicity test of Alternaria alternata, Fusarium oxysporum, Nigrospora oryzae and Cladosporium herbarum showed that disease index were 50, 25,25and 12.5 %,

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe