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TUMOR BRAIN DETECTION THROUGH MR IMAGES: A REVIEW OF LITERATURE
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Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by using different tools and techniques. However, this paper presents a comprehensive review of the methods and techniques used to detect brain tumor through MRI image segmentation. Lastly, the paper concludes with a concise discussion and provides a direction toward the upcoming trend of more advanced research studies on brain image segmentation and Tumor detection.

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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
A modified Mobilenetv2 architecture for fire detection systems in open areas by deep learning
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

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Publication Date
Sun Sep 22 2019
Journal Name
Baghdad Science Journal
Detection of CTX-M-type ESBLs from Escherichia coli Clinical Isolates from a Tertiary Hospital, Malaysia
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The present study aims to detect CTX-M-type ESBL from Escherichia coli clinical isolates and to analyze their antibotic susceptibility patterns. One hundred of E. coli isolates were collected from different clinical samples from a tertiary hospital. ESBL positivity was determined by the disk diffusion method. PCR used for amplification of CTX-M-type ESBL produced by E. coli. Out of 100 E. coli isolates, twenty-four isolates (24%) were ESBL-producers. E. coli isolated from pus was the most frequent clinical specimen that produced ESBL (41.66%) followed by urine (34.21%), respiratory (22.23%), and blood (19.05%).  After PCR amplification of these 24 isolates, 10 (41.66%) isolates were found to possess CTX-M genes. The CTX-M type ESBL

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Publication Date
Sun Jun 30 2024
Journal Name
Iraqi Journal Of Science
Detection of Zn Water Pollution by a Biosensor Based on Alkaloids Derived from Iraqi Catharanthus Roseus
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     In this work, the detection of zinc (Zn) ions that cause water pollution is studied using the CSNPs- Linker-alkaloids compound that was prepared by linking extracted alkaloids from Iraqi Catharanthus roseus plant with Chitosan nanoparticles (CSNPs) using maleic anhydride. This compound is characterized by an X-ray diffractometer (XRD) which shows that it has an orthorhombic structure with crystallite size in the nano dimension. Zeta Potential results show that the CSNPs-Linker-alkaloids carried a positive charge of 54.4 mV, which means it possesses high stability.  The Fourier transform infrared spectroscopy (FTIR) shows a new distinct band at 1708.93 cm-1 due to C=O esterification. Scanning electron microscope (SEM) image

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Overlapping Structure Detection in Protein-Protein Interaction Networks Using a Modified Version of Particle Swarm Optimization
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In today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har

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Publication Date
Fri May 03 2024
Journal Name
Optical And Quantum Electronics
Design and analysis of a dual-core PCF biosensor based on SPR for cancerous cells detection
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Publication Date
Tue Jul 11 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effect of the Six Thinking Hats Strategy on the Development of Essay Writing Skills and Creativity in It among Persian-Speaking Students Who are Studying Arabic Language and Literature At Shiraz University: Literature and Humanities, Shiraz University
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The study aims to investigate the effect of the Six Thinking Hats Strategy on the achievement of essay writing skills among third-year students in Arabic Language and Literature who are Persian speakers enrolled in the course of Essay Writing (III) at Shiraz University for the academic year 2019-2020. The sample of the study consisted of (15) male and female students who were taught according to the pre-posttest, using the quasi-experimental approach. After applying the statistical analysis on the scores of the post-test, the results showed that there are statistically significant differences in the average of students' achievement in the skills of essay writing in terms of using the Six Thinking Hats Strategy. The results also proved th

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Publication Date
Sat Feb 01 2020
Journal Name
Biochem. Cell. Arch
EVALUATION THE AVOIDANCE EFFECTS OF OXIDROXEDUCTASE AND CATECHINES FOR CATECHOL CYTOTOXICITY IN SOME TUMOR CELL LINES
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The cytotoxic effect of catechol was examined in two human cancer cell lines, Epidermoid larynx carcinoma (Hep- 2), Cerebral glioblastoma multiforme (AMGM-5) and Murine mammary adenocarcinomacell (AMN3) treated with half concentrations of catechol (1000, 500, 250, 125, 62.5 and 32.25 μM) for 72 hr. The get hold of results showed catechol have a toxic effect of the cell viability of three types of cell lines after 72h of exposure, the toxicity was dependent on catechol concentrations and/or autoxidation for quinines formation, there were a marked decreased of cell viability in a dose dependent manner in all cell line types. Inhibition concentration of catechol for 50% of cell viability (IC50) were calculated, they were at 581.5 μM, 478 μM

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Publication Date
Wed Jun 29 2022
Journal Name
Chemphyschem
Spherical Aromaticity of Tetrahedral Pnictogens Through <i>Off</i> ‐Nucleus Isotropic Magnetic Shielding
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This work revealed the spherical aromaticity of some inorganic E4 cages and their protonated E4H+ ions (E=N, P, As, Sb, and Bi). For this purpose, we employed several evaluations like (0D-1D) nucleus independent chemical shift (NICS), multidimensional (2D-3D) off-nucleus isotropic shielding σiso(r), and natural bond orbital (NBO) analysis. The magnetic calculations involved gauge-including atomic orbitals (GIAO) with two density functionals B3LYP and WB97XD, and basis sets of Jorge-ATZP, 6-311+G(d,p), and Lanl2DZp. The Jorge-ATZP basis set showed the best consistency. Our findings disclosed non-classical aromatic characters in the above molecules, which decreased from N to Bi cages. Also, the results showed more aromaticity in E4 than E4H+

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Geological Journal
A Review on Pressure Transient Analysis in Multilayer Reservoir: South Iraq Case Study
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Multilayer reservoirs are currently modeled as a single zone system by averaging the reservoir parameters associated with each reservoir zone. However, this type of modeling is rarely accurate because a single zone system does not account for the fact that each zone's pressure decreases independently. Pressure drop for each zone has an effect on the total output and would result in inter-flow and the premature depletion of one of the zones. Understanding reservoir performance requires a precise estimation of each layer's permeability and skin factor. The Multilayer Transient Analysis is a well-testing technique designed to determine formation properties in more than one layer, and its effectiveness over the past two decades has been

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Publication Date
Mon Dec 01 2025
Journal Name
Al-khwarizmi Engineering Journal
Object Dimension and Location Determination in Gantry Robots and Conveyor Systems: A Review
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A​‍​‌‍​‍‌ gantry robot is one of the most common types of industrial robots with linear movement. This type of robot is also known as a Cartesian or linear robot. It is an automated industrial system that moves along linear paths, enabling it to create a 3D envelope of the space in which it operates. A robot of this type has a standardised configuration process because it can have several sets of axes, such as X, Y and Z. The gantry robot picks up products from several places, so it can search through various locations. Afterwards, it carefully deposits the products on a conveyor belt for the next stage of the procedure or final ​‍​‌‍​‍‌shipment. This integration enables continuous and automated material flow

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