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HF Wave Propagation Prediction Based On Passive Oblique Ionosonde
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High frequency (HF) communications have an important role in long distances wireless communications. This frequency band is more important than VHF and UHF, as HF frequencies can cut longer distance with a single hopping. It has a low operation cost because it offers over-the-horizon communications without repeaters, therefore it can be used as a backup for satellite communications in emergency conditions. One of the main problems in HF communications is the prediction of the propagation direction and the frequency of optimum transmission (FOT) that must be used at a certain time. This paper introduces a new technique based on Oblique Ionosonde Station (OIS) to overcome this problem with a low cost and an easier way. This technique uses the international shortwave radio stations and the global beacons as the OIS transmitter and a normal HF receiver as the OIS receiver to verify the direction of propagation and the FOT. In addition, the critical frequency for F2 layer (fof2) was estimated in this paper for Iraq experimentally. The proposed technique was tested practically, and FOT range between Baghdad and other remote stations was estimated successfully using a radio receiver from Kenwood model R 1000 with a long wire antenna as a passive OIS system receiver.

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Tue Sep 02 2025
Journal Name
Chemistry & Biodiversity
Synthesis, In Silico, and Biological Evaluation of Non‐Hydroxamate Benzoic Acid–Based Derivatives as Potential Histone Deacetylase Inhibitors (HDACi)
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ABSTRACT<p>Unregulated epigenetic modifications, including histone acetylation/deacetylation mediated by histone acetyltransferases (HATs) and histone deacetylases (HDACs), contribute to cancer progression. HDACs, often overexpressed in cancer, downregulate tumor suppressor genes, making them crucial targets for treatment. This work aimed to develop non‐hydroxamate benzoic acid–based HDAC inhibitors (HDACi) with comparable effect to the currently four FDA‐approved HDACi, which are known for their poor solubility, poor distribution, and significant side effects. All compounds were structurally verified using FTIR, <sup>1</sup>HNMR, <sup>13</sup>CNMR, and mass spectrometry. In silico ana</p> ... Show More
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Publication Date
Fri Aug 02 2024
Journal Name
Farmacia
SOLUPLUS AND SOLUTOL HS-15 OLMESARTAN MEDOXOMIL NANOMICELLE BASED ORAL FAST DISSOLVING FILM: IN VITRO AND IN VIVO CHARACTERIZATION
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Olmesartan medoxomil (OM) has low bioavailability and limited solubility. To enhance bioavailability, fast dissolving films (FDF) with mixed micelles of soluplus (SPL) and solutol HS15 (STL H15) were developed using solvent casting. The optimised formula, FM2, used polyvinyl alcohol (PVA) and showed high entrapment efficiency, rapid disintegration, and significant improvement in OM bioavailability compared to the market tablet (Olmetec®). FM2 also demonstrated stability and potential for enhanced drug delivery.

Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Wed Oct 30 2024
Journal Name
Internet Technology Letters
Using <scp>5G</scp> Standards for Smart Healthcare Applications and Designing an Artificial Intelligence‐Based Industry 4.0 Communication System
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ABSTRACT<p>The introduction of Industry 4.0, to improve Internet of Things (IoT) standards, has sparked the creation of 5G, or highly sophisticated wireless networks. There are several barriers standing in the way of 5G green communication systems satisfying the expectations for faster networks, more user capacity, lower resource consumption, and cost‐effectiveness. 5G standards implementation would speed up data transmission and increase the reliability of connected devices for Industry 4.0 applications. The demand for intelligent healthcare systems has increased globally as a result of the introduction of the novel COVID‐19. Designing 5G communication systems presents research problems such as optimizing </p> ... Show More
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Publication Date
Sun Mar 01 2020
Journal Name
Iraqi Journal Of Physics
Study the performance of pentacene based organic field effect transistor by using monolayer, bilayer and trilayer with different gate insulators
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In this paper, Pentacene based-organic field effect transistors (OFETs) by using different layers (monolayer, bilayer and trilayer) for three different gate insulators (ZrO2, PVA and CYEPL) were studied its current–voltage (I-V) characteristics by using the gradual-channel approximation model. The device exhibits a typical output curve of a field-effect transistor (FET). Source-drain voltage (Vds) was also investigated to study the effects of gate dielectric on electrical performance for OFET. The effect of capacitancesemiconductor in performance OFETs was considered. The values of current and transconductance which calculated using MATLAB simulation. It exhibited a value of current increase with increasing source-drain voltage.

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Publication Date
Fri Jun 30 2023
Journal Name
Pakistan Heart Journal
Music Medicine Intervention--Based Program for Reducing Pain and Anxiety of Children Undergoing Bone Marrow Aspiration and Lumber Puncture Procedures
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Publication Date
Sun Dec 22 2019
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Prevalence of UGT1A1*93 and ABCC5 Polymorphisms in Cancer Patients Receiving Irinotecan-Based Chemotherapy at Al-Najaf Al-Ashraf
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Irinotecan (CPT-11) is a semisynthetic derivative of the antineoplastic agent camptothecin used in a wide range as an anti-cancer agent in many solid tumors because of its cytotoxic effect through the interaction with the topoisomerase I enzyme. The major limiting factors for irinotecan treatment are its association with potentially life-threatening toxicities including neutropenia and acute or delayed-type diarrhea, results from distinct interindividual and interethnic variability due to gene polymorphism.

This is a cross sectional pharmacogentics study was conducted on 25 cancer patients to estimate the prevalence of UGT1A1*93 and ABCC5 allele single nucleotide polymorphism (SNP) in Iraqi cancer patients treated with irinotecan

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Publication Date
Sun Sep 04 2016
Journal Name
Baghdad Science Journal
Degradation of Brilliant Green by Using a bentonite Clay- Based Fe Nano Composite Film as a Heterogeneous Photo- Fenton Catalyst.
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This paper aims to study the chemical degradation of Brilliant Green in water via photo-Fenton (H2O2/Fe2+/UV) and Fenton (H2O2/Fe2+) reaction. Fe- B nano particles are applied as incrustation in the inner wall surface of reactor. The data form X- Ray diffraction (XRD) analysis that Fe- B nanocomposite catalyst consist mainly of SiO2 (quartz) and Fe2O3 (hematite) crystallites. B.G dye degradation is estimated to discover the catalytic action of Fe- B synthesized surface in the presence of UVC light and hydrogen peroxide. B.G dye solution with 10 ppm primary concentration is reduced by 99.9% under the later parameter 2ml H2O2, pH= 7, temperature =25°C within 10 min. It is clear that pH of the solution affects the photo- catalytic degradation

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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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