Ayman Yousif - Academia.edu (original) (raw)

Papers by Ayman Yousif

Research paper thumbnail of Applying reinforcement learning for random early detaction algorithm in adaptive queue management systems

Indonesian Journal of Electrical Engineering and Computer Science

Recently, the use of internet has been increased all around the hose, the companies, government d... more Recently, the use of internet has been increased all around the hose, the companies, government departments and the video games and so on. Thus, this increased the traffic used in the networks, which generated congestion issues and sent packet drop in the nodes. To solve this problem, certain algorithms are used. The Active queue management is one of the most important algorithms that helps with this issue. For an effective network management, the RL was used, and it will adapt with the parameters of algorithms. Where the suggested algorithm deep Q-networks (DQN) depends on the reinforcement learning (RL) to reduce the drop and delay. Also, the random early detection (RED) (an active queue management (AQM) algorithm) was adopted based on the NS3 situation.

Research paper thumbnail of A logistic model of early pregnancy ultrasound measurements and prediction of first-trimester outcome

Minia Journal of Medical Research

Background: In early pregnancy, it is essential to emphasize viability and gestational age precis... more Background: In early pregnancy, it is essential to emphasize viability and gestational age precisely. Researchers tried to discover some useful sonographic indicators in early pregnancy so as to expect the outcome of the ongoing pregnancy. The aim of this study is to assess firsttrimester ultrasound measurements for the prediction of early pregnancy loss. Method: This is a prospective observational cohort study done in the outpatient clinic of obstetrics and gynecology of El Minia maternity university hospital from 1st February-31st August 2021. A random sample of 143 pregnant women selected, 7 were lost to follow up. For the 136 pregnant women followed 9(6.6%) had early pregnancy loss, and 127(93.4%) continue pregnancy after 12 weeks. Results: 136 pregnant women examined by using transvaginal ultrasonography. The readings at 6th week of gestation for the (GSD, YSD, CRL, and FHR) were (13.05± 1.17), (2.88± 1.62), (2.79± 0.72), & (94.5± 9.54) respectively, lower among those with first trimester loss than those continue pregnancy (28.71± 5.72), (4.29± 0.33), (5.61± 0.55), and (130.9± 3.3). The readings at 12th week of gestation for the (GSD, YSD, CRL, and FHR) were as follows; [(22.59± 3.15), (3.24± 0.27), (11.7± 1.59). & (148.5± 0.9)] were lower among with first trimester loss group than those continue pregnancy [(65.12± 4.51), (4.95± 0.77), (55.77± 6.27) & (188.1± 5.5)]. Conclusions: The current study found that lower Gestational Sac Diameter, Youlk Sac Diameter, Crown-Rump Length, and Fetal Heart Rate may indicate early pregnancy loss.

Research paper thumbnail of Applying reinforcement learning for random early detaction algorithm in adaptive queue management systems

Indonesian Journal of Electrical Engineering and Computer Science

Recently, the use of internet has been increased all around the hose, the companies, government d... more Recently, the use of internet has been increased all around the hose, the companies, government departments and the video games and so on. Thus, this increased the traffic used in the networks, which generated congestion issues and sent packet drop in the nodes. To solve this problem, certain algorithms are used. The Active queue management is one of the most important algorithms that helps with this issue. For an effective network management, the RL was used, and it will adapt with the parameters of algorithms. Where the suggested algorithm deep Q-networks (DQN) depends on the reinforcement learning (RL) to reduce the drop and delay. Also, the random early detection (RED) (an active queue management (AQM) algorithm) was adopted based on the NS3 situation.

Research paper thumbnail of A logistic model of early pregnancy ultrasound measurements and prediction of first-trimester outcome

Minia Journal of Medical Research

Background: In early pregnancy, it is essential to emphasize viability and gestational age precis... more Background: In early pregnancy, it is essential to emphasize viability and gestational age precisely. Researchers tried to discover some useful sonographic indicators in early pregnancy so as to expect the outcome of the ongoing pregnancy. The aim of this study is to assess firsttrimester ultrasound measurements for the prediction of early pregnancy loss. Method: This is a prospective observational cohort study done in the outpatient clinic of obstetrics and gynecology of El Minia maternity university hospital from 1st February-31st August 2021. A random sample of 143 pregnant women selected, 7 were lost to follow up. For the 136 pregnant women followed 9(6.6%) had early pregnancy loss, and 127(93.4%) continue pregnancy after 12 weeks. Results: 136 pregnant women examined by using transvaginal ultrasonography. The readings at 6th week of gestation for the (GSD, YSD, CRL, and FHR) were (13.05± 1.17), (2.88± 1.62), (2.79± 0.72), & (94.5± 9.54) respectively, lower among those with first trimester loss than those continue pregnancy (28.71± 5.72), (4.29± 0.33), (5.61± 0.55), and (130.9± 3.3). The readings at 12th week of gestation for the (GSD, YSD, CRL, and FHR) were as follows; [(22.59± 3.15), (3.24± 0.27), (11.7± 1.59). & (148.5± 0.9)] were lower among with first trimester loss group than those continue pregnancy [(65.12± 4.51), (4.95± 0.77), (55.77± 6.27) & (188.1± 5.5)]. Conclusions: The current study found that lower Gestational Sac Diameter, Youlk Sac Diameter, Crown-Rump Length, and Fetal Heart Rate may indicate early pregnancy loss.