Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, coronal plane, and sagittal plane. Three different thresholds, which are based on texture features: mean, energy and entropy, are obtained automatically. This allowed to accurately separating the MRI slice into normal and abnormal one. However, the abnormality detection contained some normal blocks assigned wrongly as abnormal and vice versa. This problem is surmounted by applying the fine-tuning mechanism. Finally, the MRI slice abnormality detection is achieved by selecting the abnormal slices along its tumour region (Region of Interest-ROI).
The Sebkha is considered the evaporative geomorphological features, where climate plays an active role. It forms part of the surface features in Mesopotamia plain of Iraqi, which is the most fertile lands, and because of complimentary natural and human factors turned most of the arable land to the territory of Sebkha lands. The use satellite image (Raw Data), Landsat 30M Mss for the year 1976 Landsat 7 ETM, and the Landsat 8 for year 2013 (LDCM) for the summer Landsat Data Continuity Mission and perform geometric correction, enhancements, and Subset image And a visual analysis Space visuals based on the analysis of spectral fingerprints earth's This study has shown that the best in the discrimination of Sebkha Remote sensing techniques a
... Show MoreConvolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,
... Show MoreThis study aimed at revealing the degree of availability of standards of word problems in mathematics books for the first three grades of the basic stage in Palestine. For this purpose, the researcher prepared an analysis tool and a list of criteria consisting of two areas: linguistic formulation and mathematical content. Every area had seven items. The results of the study showed that the third-grade mathematics book has the highest degree of availability of the standards with 85.75%, and then came the second-grade mathematics book with 83.12%. Finally, the first-grade mathematics book came with 80.13%. In the light of the previous results, the researcher recommended to develop the language of word problems, to take into account their i
... Show MoreThis study investigates the characterization and growth dynamics of a Magnetically Stabilized Gliding Arc Discharge (MSGAD) system, generating non-thermal plasma with argon gas under atmospheric pressure and flow rates of 1-5 L/min. The electrical properties and growth patterns concerning gas flow rates and applied voltages were examined utilizing a magnetic field for stability. Using a digital oscilloscope, a correlation between voltage reduction and increased current was uncovered. An algorithm analyzes digital images to compute arc length, area, and volume. Results reveal how gas flow rate and applied voltage directly impact arc growth. Furthermore, the magnetic field's role in guiding and stabilizing the plasma discharge was explored. T
... Show MoreThe aim of this work is studying the binary system ??'??? Ni?)with two ratios (y=36,80) by using casting method for preparing the samples.Magnetic and Mechanical properties have been studidt different httrea^nttem^rature.All the alloys were found a ferromagnetic behavior and sensitive to the heat treatment. Best properties were found at the heat treatment 1100 C°.A significant different results were found above 1100C° for lower magnetic and mechanical values. This is possibly due to the change on the degree of magnetic moment orders, in which most of the moments are started to remove from coupled ferromagnetically.?
Inelastic magnetic electron scattering M1 at Ex =10.23 MeV form factors in Ca-48 have been investigated. The fp shell model space with four orbits and eight neutrons have been considered and FPD6 has been selected between 32 model space effective interactions to generates the model space vectors for the M1 transition with excitation energy Ex =10.23 MeV and for constructing OBDM. Discarded space (core and higher configuration orbits) has been included through the first order perturbation theory to couple the partice-hole pair of excitation in the calculation of the total M1 form factor and regarding the realistic interaction M3Y as a core polarization interaction with six sets of fitting parameters. Finally the theoretical calculations h
... Show MoreOff-nucleus isotropic magnetic shielding (σiso(r)) and multi-points nucleus independent chemical shift (NICS(0-2 Å)) index were utilized to find the impacts of the isomerization of gas-phase furfuraldehyde (FD) on bonding and aromaticity of FD. Multidimensional (1D to 3D) grids of ghost atoms (bqs) were used as local magnetic probes to evaluate σiso(r) through gauge-including atomic orbitals (GIAO) at density functional theory (DFT) and B3LYP functional/6-311+G(d,p) basis set level of theory. 1D σiso(r) responses along each bond of FD were examined. Also, a σiso(r) 2D-scan was performed to obtain σiso(r) behavior at vertical heights of 0–1 Å above the FD plane in its cis, transition state (TS) and trans forms. New techniques fo
... Show More