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Immobilization of cobalt ions using hierarchically porous 4A zeolite-based carbon composites: Ion-exchange and solidification
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Publication Date
Wed Sep 25 2013
Journal Name
International Journal For Sciences And Technology
Synthesis, Characterization, And Antibacterial Activities Of Manganese (II),Cobalt(II), Copper(II) ,Iron (II), Nickel (II) And Cadmium(II) Mixed- Ligand Complexes Containing Amino Acid( L- Lysine) And 1,10-Phenanthroline
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The research includes the synthesis and identification of the mixed ligands complexes of M(II) Ions in general composition [M(Lyn)2(phen)] Where L- lysine (C6H14N2O2) commonly abbreviated (LynH) as a primary ligand and 1,10-phenanthroline(C12H8N2) commonly abbreviated as "phen," as a secondary ligand . The ligands and the metal chlorides were brought in to reaction at room temperature in ethanol as solvent. The reaction required the following molar ratio [(1:1:2) (metal): phen:2 Lyn -] with M(II) ions, were M = Mn(II),Cu(II), Ni(II), Co(II), Fe(II) and Cd(II). Our research also includes studying the bio–activity of the some complexes prepared against pathogenic bacteria Escherichia coli(-),Staphylococcus(-) , Pseudomonas (-), Bacillus (-)

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Antimicrobial Activity of Locally Synthesized Carbon Nanosphere on Some Pathogenic Species of Bacteria and Parasites
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Antibacterial activity of CNSs against Staphylococcus aureus and Escherichia coli was estimated. Higher inhibition zone of 18 mm and 20 mm were observed against S. aureus and E.coli, respectively, at a concentration of 2 mg/ml of carbon nanosphere after 24 hrs of incubation at 37 ºC. In vitro cytotoxicity experiment was performed on two parasite strains of Leishmania donovani and Leishmania tropica by using MTT assay. L. donovani revealed more sensitiv to the CNSs than L. tropica. An intermediate level of cytotoxicity of 51.31 % was observed when 2.4 mg/ml of CNSs was incubated with L. donovani, while weak cytotoxicity of 37.20 % was shown when the

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Publication Date
Tue May 01 2012
Journal Name
Iraqi Journal Of Physics
Studying the effect of temperature and treating time on some physical properties of carbon black
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Samples prepared by using carbon black as a filler material and phenolic resin as a binder. The samples were pressed in a (3) cm diameter cylindrical die to (250)MPa and treated thermally within temperature range of (600-1000)oC for two and three hours. Physical properties tests were performed, like density, porosity, and X-ray tests. Moreover vicker microhardness and electric resistivity tests were done. From the results, it can be concluded that density was increased while porosity was decreased gradually with increasing temperature and treating time. In microhardness test, it found that more temperature and treating time cause more hardness. Finally the resistivity was decreased in steps with temperature and treating time. It can be c

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
The Effect of Walled Nano-Carbon on the Physical, Thermal and Mechanical Properties of Epoxy
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The physical, the thermal and the mechanical properties of Nano-composites, that consisted of Polyprime EP epoxy that reinforced by multi-walled carbon nanotubes (MWCNTs), have been studied. Various loading ratios, 0.1, 0.5, and 1 wt. %of MWCNT shave been infused into epoxy by a magnetic stirrer and then the hardener mixed with the mthat supplied with the epoxy. All sample shave been cutting using CNC machine. Tensile test, three-point bending, hardness tests, lee's disk, differential scanning calorimetry, water absorption and dielectric and electrical conductivity test were utilized on unfilled, MWCNT-filled epoxy to identify the loading effect on the properties of materials. Scanning electron microscopy (SEM) was used to determine the

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Publication Date
Tue Dec 05 2017
Journal Name
International Journal Of Science And Research (ijsr)
Multi Response Optimization of Submerged Arc Welding Using Taguchi Fuzzy Logic Based on Utility Theory
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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Science
Synthesis, Characterization, Thermal Studies, and Antioxidant Activities of Azo Dye[2-[(3-Hydroxyphenyl)diazinyl]-1,2-Benzothiazol-3(2H)-one-1,1-Dioxide]and Metal Ion Complexes
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The new azo dye was synthesized via the reaction of the diazonium salt form of 3-aminophenol with 2-hydroxyquinoline. This dye was then used to access a series of complexes with the chlorides of manganese, iron, zinc, cadmium, and vanadium sulfate. The prepared ligand and its complexes were characterized by FT-IR spectroscopy, UV-visible spectroscopy, mass spectrometry, thermogravimetric analysis, differential scanning calorimeter, and microelemental analysis. Conductivity, magnetic susceptibility, metal content, and chlorine content of the complexes were also measured. The ligand and cadmium complex were identified using1H NMR and 13C NMR spectroscopy. The results showed that the shape of the ligand is a trigonal planner, and the c

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Robot Arm Path Planning Using Modified Particle Swarm Optimization based on D* algorithm
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Abstract

Much attention has been paid for the use of robot arm in various applications. Therefore, the optimal path finding has a significant role to upgrade and guide the arm movement. The essential function of path planning is to create a path that satisfies the aims of motion including, averting obstacles collision, reducing time interval, decreasing the path traveling cost and satisfying the kinematics constraints. In this paper, the free Cartesian space map of 2-DOF arm is constructed to attain the joints variable at each point without collision. The D*algorithm and Euclidean distance are applied to obtain the exact and estimated distances to the goal respectively. The modified Particle Swarm Optimization al

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Publication Date
Sat Aug 02 2025
Journal Name
Engineering, Technology & Applied Science Research
A New Method for Face-Based Recognition Using a Fuzzy Face Deep Model
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Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

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Publication Date
Sun Apr 02 2023
Journal Name
Narst 2023 Annual International Conference
Measuring Claim-Evidence-Reasoning Using Scenario-based Assessments Grounded in Real-world Issues
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Improving students’ use of argumentation is front and center in the increasing emphasis on scientific practice in K-12 Science and STEM programs. We explore the construct validity of scenario-based assessments of claim-evidence-reasoning (CER) and the structure of the CER construct with respect to a learning progression framework. We also seek to understand how middle school students progress. Establishing the purpose of an argument is a competency that a majority of middle school students meet, whereas quantitative reasoning is the most difficult, and the Rasch model indicates that the competencies form a unidimensional hierarchy of skills. We also find no evidence of differential item functioning between different scenarios, suggesting

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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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