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A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comparison to the actual observational results. ANN simulation gives a clear insight into three crescent moon visibility regions: invisible (I), probably visible (P), and certainly visible (V). The proposed ANN is suitable for building lunar calendars, so it was used to build a four-year calendar on the horizon of Baghdad. The built calendar was compared with the official Hijri calendar in Iraq.

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Publication Date
Mon Aug 01 2022
Journal Name
Journal Of Engineering
Production of Load Bearing Concrete Masonry Units (blocks) From Green Concrete Containing Plastic Waste and Nano Silica Sand Powder
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Industrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m3 (B-400) to 300 kg/m3 (B-300) then to 200 kg/m3 (B-200). While (B-380) was produced using 380 kg/m3 cement and 20 kg/m3 nano-sil

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Thermophysical properties of [EMIM][BF<sub>4</sub>] and [HMIM][PF<sub>6</sub>] imidazolium ionic liquids with MWCNTs
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Abstract<p>In this study, several ionanofluids (INFs) were prepared in order to study their efficiency as a cooling medium at 25 °C. The two-step technique is used to prepare ionanofluid (INF) by dispersing multi-walled carbon nanotubes (MWCNTs) in two concentrations 0.5 and 1 wt% in ionic liquid (IL). Two types of ionic liquids (ILs) were used: hydrophilic represented by 1-ethyl-3-methylimidazolium tetrafluoroborate [EMIM][BF<sub>4</sub>] and hydrophobic represented by 1-hexyl-3-methylimidazolium hexafluorophosphate [HMIM][PF<sub>6</sub>]. The thermophysical properties of the prepared INFs including thermal conductivity (TC), density and viscosity were measured experimental</p> ... Show More
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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
Sat Jun 01 2024
Journal Name
Results In Engineering
Thermodynamic modeling and performance analysis of photovoltaic-thermal collectors integrated with phase change materials: Comprehensive energy and exergy analysis
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Publication Date
Tue Nov 01 2022
Journal Name
Inorganic Chemistry Communications
Sustainable adsorptive removal of high concentration organic contaminants from water using biodegradable Gum-Acacia integrated magnetite nanoparticles hydrogel adsorbent
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Release of industrial effluents comprising dyes in water bodies is one of the foremost causes of water pollution. Therefore, the proper and proficient treatment of these dyes contaminated left-over material before their release is crucial. Herein, an eco-friendly biological macromolecule Gum-Acacia (GA) integrated Fe3O4 nanoparticles composite hydrogel was manufactured via co-precipitation technique for effective adsorption of Congo red (CR) dye existing in water bodies. The as-prepared magnetic GA/Fe3O4 composite hydrogel was characterized by FTIR, XRD, EDX, VSM, SEM, and BET techniques. These studies discovered the fruitful fabrication of biodegradable magnetic GA/Fe3O4 composite hydrogel possessing porous structure with large surface are

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Publication Date
Tue Jun 16 2020
Journal Name
Frontiers In Pharmacology
Administration of Δ9‐Tetrahydrocannabinol (THC) Post‐Staphylococcal Enterotoxin B Exposure Protects Mice From Acute Respiratory Distress Syndrome and Toxicity
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Publication Date
Wed May 13 2020
Journal Name
Journal Of Plant Nutrition
Seed priming of sorghum cultivars by gibberellic and salicylic acids to improve seedling growth under irrigation with saline water
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An experiment was conducted in pots under field conditions during fall seasons of 2017 and 2018. This study aimed to improve a weak growth of seedlings under salt stress in sorghum. Three factors were studied. 1st factor was three cultivars (Inqath, Rabeh, and Buhoth70). 2nd factor was seed priming (primed and unprimed seed). Seed were primed by soaking for 12 hours in a solution containing 300 + 70 mg L−1 of gibberellic (GA3) and salicylic (SA) acids, respectively. 3rd factor was irrigation with saline water (6, 9 and 12 dS m−1) resulting from dissolving sodium chloride in distilled water in addition to control treatment (distilled water). Randomized complete block design was used with four replications. In both seasons: the results sh

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Publication Date
Wed Oct 01 2025
Journal Name
Journal Of Materials Science: Materials In Electronics
Comprehensive study of Cu2⁺-ion conducting PVA/PVP/glycerin-based gel polymer electrolytes: structural, electrical, dielectric, and optical properties
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This study investigates the impact of copper sulfate (CuSO4) doping and glycerin plasticization on the structural, electrical, dielectric, and optical properties of poly(vinyl alcohol) (PVA), polyvinyl pyrrolidone (PVP), and glycerin gel polymer electrolytes (GPEs). The GPEs were prepared using a solution casting method with varying CuSO4 concentrations (5 and 10 wt.%). X-ray diffraction analysis revealed the semi-crystalline nature of the polymer blend and also confirmed the presence of CuSO4. Fourier transform infrared spectroscopy confirmed the miscibility of PVA, PVP, and glycerin through interchain hydrogen bonding and indicated the successful incorporation of Cu2+ ions into the polymer blend matrix. The PVA/PVP/glycerin blend containi

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Publication Date
Sun Aug 16 2026
Journal Name
Journal Of Esthetic And Restorative Dentistry
Effectiveness of Cellulose Nanofibers Addition to Soft Denture Lining Material on Candida albicans Adherence and Physical and Mechanical Properties
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Purpose: Current denture liner materials suffer from low tear strength, poor abrasion resistance, weak bond strength to denture material, and increasing risk of denture stomatitis due to adherence. The aim of this study was to evaluate the effects of the addition of cellulose nanofibers (CNFs) to commercial soft denture liner material on the adherence of and physical and mechanical properties. Materials and Methods: CNFs at concentrations of 0.0, 0.5, and 1.0 wt.% were incorporated into a soft liner material. Antifungal effects were assessed by quantifying the adherence of . The Shore A hardness, tensile strength, peel bond strength, and surface roughness tests were employed to assess the properties of the denture liner materials. Chemica

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Publication Date
Fri Mar 16 2012
Journal Name
Iraqi National Journal Of Chemistry
Spectroscopic and Biological activity studies of azo ligand type (N,O)and its complexes with CrIII, MnII and FeII ions
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Azo derivative ligand[H3L] have been synthesized by the reaction of diazonium salt of p-amino benzoic acid with orcinol in(1:1)mole ratio. The bidente ligand was reacted with the metal ions MnII,FeIIandCrIIIin(2:1)mole ratio via reflux in ethanol using Et3N as a base to give complexes of the general formula: [ M(H2L)2(H2O)x]Cly The synthesized compounds were characterized by spectroscopic methods[ I.R , UV-Vis, A.A and H1 NMR]along with melting point, chloride content and conductivity measurements. The complexes were screend for their in vitro antibacterial activity against one strain of staphylococcus as Gram(+) positive and one strain of pseudomonas as Gram(-) Negative, using the agar diffusion technique.