This study sought to give a general picture of the organizations and formations of the ground forces of the Abbasid army in its first era, in preparation and armament and continuous development of the mechanisms to help maintain the moral and spiritual morale in the fighting.
Therefore, the caliphs' interest in building the army, organizing it, arming it, choosing competent leaders, and providing them with various weapons in terms of production and storage, as well as taking care of fortifying the cities and gaps in determination and determination, and embarked on construction and restoration, where amazing speed and acted according to the circumstances. During the first Abbasid era, there were significant developments in the military

The  insect is diagnosed and named by the National Center of Biotechnology Information (NCBI), USA as the Mint leaf Beetle Chrysolina herbacea alnadawi (Duftschmid, 1825), (Coleoptera: Chrysomelidae). The diagnosis was performed depending on the DNA analysis by 73% similarity with Chrysolina herbacea (Duftschmid, 1825) sequence, In the present study. It is recorded as a new insect pest on mint plant Mentha  puleguim (L,1753) (Lamiaceae). DNA analysis confirmend that it is recorded for the first time in Iraq and the Arab world as well as the Middle East. Those insects were observed initially during August 2017 in residential gardens of Al-Bonooq district in Baghdad / Iraq.

Parasitological examination of gills of three species of sparid fishes in the territorial waters of Iraq was performed, two diplectanid monogenoids were isolated and described; Lamellodiscus indicus Tripathi, 1959 from both Haffara seabream Rhabdosargus haffara (Forsskål, 1775) and Goldline seabream R. sarba (Forsskål, 1775) and Protolamellodiscus senilobatus Kritsky, Jiménez-Ruiz and Sey, 2000 from King soldierbream Argyrops spinifer (Forsskål, 1775). The record of the parasites is considered new to the parasite fauna of Iraq. The redescription of L. indicus for the first time which is collected from a new distribution area (Arabian Gulf). R. haffara is considered a new host record .

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

Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

Traffic management at road intersections is a complex requirement that has been an important topic of research and discussion. Solutions have been primarily focused on using vehicular ad hoc networks (VANETs). Key issues in VANETs are high mobility, restriction of road setup, frequent topology variations, failed network links, and timely communication of data, which make the routing of packets to a particular destination problematic. To address these issues, a new dependable routing algorithm is proposed, which utilizes a wireless communication system between vehicles in urban vehicular networks. This routing is position-based, known as the maximum distance on-demand routing algorithm (MDORA). It aims to find an optimal route on a hop-by-ho

In this research, Schiff bases derived from the reaction of anthrone with different heterocyclic amines have been described. The resulted Schiff base compounds were reacted with various nucleophiles in order to obtain new heterocyclic derivatives. Chemical structures of all products were confirmed by IR, 1H-, 13C-NMR spectral data and elemental analysis. All synthesized compounds were in vitro tested against a standard strain of pathogenic microorganism including Gram +ve bacteria (Staphylococcus aureus), Gram –ve bacteria (Escherichia coli), and fungi (Candida albicans).