In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

Young people represent the power and cornerstone of societies and their superiority is linked to their well-being. Their empowerment is as essential as the heart to the body, if it is corrupt, then the whole body is corrupt, and vice versa. The exposure to extremism and pressure from their families leads to violent acts and crimes for obtaining money through unknown organized bodies. This will drive them to fail in their life in an attempt to fulfill their most basic needs, which they have been deprived of by their families, the government, and other institutions. Therefore, governments should provide job opportunities for young people and provide entertainment centers, sports clubs, and family education centers that raise awareness of s

Intrusion detection system is an imperative role in increasing security and decreasing the harm of the computer security system and information system when using of network. It observes different events in a network or system to decide occurring an intrusion or not and it is used to make strategic decision, security purposes and analyzing directions. This paper describes host based intrusion detection system architecture for DDoS attack, which intelligently detects the intrusion periodically and dynamically by evaluating the intruder group respective to the present node with its neighbors. We analyze a dependable dataset named CICIDS 2017 that contains benign and DDoS attack network flows, which meets certifiable criteria and is ope

Background: Although iron chelation therapies have been available for many years for thalassemia intermedia patients, iron accumulation remains the major cause of death. Therefore, the need for additional chelation options is in demand. This randomized controlled study aimed to understand the effects of green tea on iron balance in thalassemia intermedia patients.

Methods: Using a random selection method, 141 thalassemia intermedia patients were initially screened for inclusion in this trial; only 68 patients included after applying exclusion criteria. Two equal groups were generated (n=34/group): green tea (three cups/day after meals) + usual treatment (deferasirox iron chelat

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

The aim of the present research is to study different protein fractions in sera of children and adolescent with  β –thalassemia major and minor and to compare the results with that of healthy control.One hundred fifty children and adolescents were enrolled in this study,including 50 patients with β- thalassemia major , 50 patients with  β- thalassemia minor as pathological control group and another apparently 50 healthy individuals as a control group. The age of all studied  groups ranged from (4-18)years.Total protein, albumin and immunoglobulins were estimated in sera of all subjects.  A Significant  decrease  was  found  in  the  total  protein and  albumin&nb

Background: Opportunistic viral infections make an important threat to renal transplantation recipients (RTRs), and with the use of more intense newly-developed immunosuppressive drugs; the risk of renal allograft loss due to reactivation of these viruses has increased considerably. At the top priority of these viruses lie BK polyomavirus (BKV) and human cytomegalovirus (CMV). Reactivation of these viruses in these chronically immunosuppressed RTRs can lead to renal impairment and subsequently allograft loss, unless early detected and properly treated. Objectives: The study aimed to detect and quantify plasma viral load of BKV and CMV in RTRs using quantitative real time PCR (qRT-PCR), in order to study the prevalence of these two viruses i