In an intensive study of the various species of the Euglenophyceae under different environmental conditions, the algal samples were collected monthly in twelve springs and six related streams from September 2019 to August 2020 within Shaglawa district-Erbil Province in virgin areas for phycolimnological study. Twenty species of Euglenophyceaen are identified as a new record for the algal flora. These taxa consist of Colacium vesiculosum, Lepocinclis salina and L.wangi, Eutreptia viridis, Euglena chlamydophora, E. clavata, E. geniculata, E. intermedia var klebsii, E. limnophila, E. oblonga, E. sociabilis, E. stellate and E. variabilis, Peranema sacculus, Phacus circumflexus, Ph. dangeardii, Ph. peteloti, Petalomonas mediocanella var disomata, Trachelomonas manginii, and T. volvocina var derephora. All of these new records are described and illustrated as much as possible. According to physicals and chemicals characteristics, water temperature varied from 14.942˚C to 18.475˚C, pH lies on alkaline side of neutrality, electrical conductivity ranged between (627.472-2092.306µs/cm) and high concentration of salinity recorded in Azarian spring.
The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t
المستودع الرقمي العراقي. مركز المعلومات الرقمية التابع لمكتبة العتبة العباسية المقدسة
This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K
... Show MoreThis research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche
... Show MoreType 2 diabetes mellitus (T2DM) is a chronic disorder that is a serious health concern all over the globe, it is linked to Interleukin-10 (IL-10) single nucleotide polymorphisms (SNPs) at the promoter region. On the other hand, diabetes influences the cellular and humoral immunity predisposing the patient to a variety of opportunistic parasites one of them is Toxoplasma gondii (T. gondii), which may infect any nucleated cell, including pancreatic cells. The purpose of this research was to explore the association of IL-10 genetic polymorphisms with T2DM and latent toxoplasmosis among Iraqi patients with T2DM. Fifty-five and fifty-eight venous blood samples were taken from T2DM patients and age-matched non-diabetic person
... Show MoreThe relationship between music and plastic arts can be viewed as an interdependent relationship, as they both develop imagination, focus and sensory perception, as well as the presence of some artistic concepts that music shares with the art of drawing, on this basis the rationale for this research aimed at identifying (the influence of music) was dealt with On the artistic output (drawing) of students of the Department of Art Education - College of Fine Arts) In the first chapter the problem of research, importance, terminology, boundaries and goal was addressed, and in the second chapter the researcher dealt with in the first topic the relationship between music and painting, and in the second topic the use of music in education. As fo
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