Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

Background: Apexification is a method to induce a calcified barrier in a root with an open apex or the continued apical development of an incomplete root in teeth with necrotic pulp. MTA apexification has several advantages such as it neither gets resorbed, nor weakens the root canal dentin, and also sets in the wet environment. The aim of this study is to evaluate the effectiveness of the use of MTA in apexification and periapical healing of teeth with incomplete root formation and periapical infection. Materials and method: Apexification was carried out on fourteen permanent immature teeth of eleven children aged 7-12 years attended the teaching hospital of College of Dentistry, Baghdad University using mineral trioxide aggregate followed

The power generation of solar photovoltaic (PV) technology is being implemented in every nation worldwide due to its environmentally clean characteristics. Therefore, PV technology is significantly growing in the present applications and usage of PV power systems. Despite the strength of the PV arrays in power systems, the arrays remain susceptible to certain faults. An effective supply requires economic returns, the security of the equipment and humans, precise fault identification, diagnosis, and interruption tools. Meanwhile, the faults in unidentified arc lead to serious fire hazards to commercial, residential, and utility-scale PV systems. To ensure secure and dependable distribution of electricity, the detection of such ha

Background: Acute leukemias (ALs) are a heterogeneous group of malignancies with various clinical, morphological, immunophenotypic, and molecular characteristics. Distinguishing between lymphoid and myeloid leukemia is often performed by flow cytometry. This study aimed to evaluate the immunophenotypic characterization and expression of immuno-markers in both acute myeloid leukemia (AML-M0) and acute T-cell lymphoblastic leukemia (T-ALL).

Methods: A retrospective cross-sectional study was conducted in the Pathology Department/Teaching Laboratories/Medical City/Iraq and included all patients newly diagnosed with AL from 5 January to 10 December 2018. Immunophenotypic analysis wa

Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

This study was aimed to investigate the response of two types of ornamental herbaceous plants (Wedelia trilobata and Jacobaea maritima 'Cirrus') to different agricultural environments and the application of potassium silicates to the living walls system LWS (Felt layer system) under the climate conditions of Baghdad city. Each experiment involved the cultivation of a different plant species, and the study duration was from September 15, 2021, to August 1, 2022. A Strip-Plot Design experiment was conducted using two factors: factor M with four levels of substrates (50% peatmoss and perlite (M1), 50% Vermicompost and perlite (M2), 50% Water hyacinth compost and perlite (M3), 50% wheat straw compost and perlite (M4)) and factor S with

BN Rashid