In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

The aim: In this study, we present and evaluate the vest-over-pants technique as a simple way to correct urethrocutaneous fistulas after hypospadias. Materials and methods: Between October 2018 and June 2020, twenty male patients aged 5 to 20 years came to us with post hypospadias repair fistula, these patients underwent vest-over-pant repair of their fistula. The size of fistula was ranging between 2.5-5 mm. The distribution of fistula was coronal (3 patients), distal penile (9 patients), midshaft (2 patients) and proximal penile (6 patients). In 14 patients there were single fistula and 6 patients had more than one fistula. Eleven of patients were exposed to a previous failed fistula repair procedure. Results: Six months after the operati

Background: Cholecystectomy in cirrhotic patients is commonly followed by high morbidity and mortality, the incidence of hepatic cirrhosis has increased since last decade as well as the occurrence of complication such as liver failure, portal hypertension, and biliary disorders.
Patients and methods: laparoscopic Cholecystectomy was performed in 24 cirrhotic patients (18 child A and 6 child B) in an effort to obtain lower complications and mortality rates. The mean age of the group was 51.8 years, ten of the 24 patients were men and 14 female.
Results: intraoperative complications such as bleeding, dense adhesion and long operative time were recorded.
Conclusion: laparoscopic Cholecystectomy was safe and

Backgrond: One of the major causes of impaired movements post-stroke is the abnormal phasing of paralytic muscles. Many studies suggested that inappropriate muscle phasing may be associated with enhanced transmission in the monosynaptic Group Ia afferent pathway in the affected limb of post-stroke patients and Group Ia reflexes are abnormally elevated and fail to decrease in amplitude during locomotion.

Objectives: This study was conducted to identify the changes in the Soleus muscle H-reflex excitability at rest in the affected lower limb of post-stroke patients as compared to the contra lateral side and of normal controls.

Patients and methods: The excitability of the m

Background: Many countries recommend the use of long-acting reversible contraceptive intrauterine device immediately after cesarean delivery. The cesarean delivery rate in Iraqi public hospitals is 32.2% and may reach 85.8% in private hospitals. Immediate post-partum intrauterine device insertion at cesarean is rarely done in Iraq.

Objectives: To assess the safety and practicality of immediate post-partum intrauterine device insertion during cesarean delivery for family planning and pregnancy spacing in Iraqi women.

Subjects and Methods: A single arm clinical trial included 150 eligible women who attended Al-‎Elwiyah Maternity Teaching Hospital or Al Hayat Rahibat Hospita

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a local

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr