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).
There are many aims of this book: The first aim is to develop a model equation that describes the spread of contamination through soils which can be used to determine the rate of environmental contamination by estimate the concentration of heavy metals (HMs) in soil. The developed model equation can be considered as a good representation for a problem of environmental contamination. The second aim of this work is to design two feed forward neural networks (FFNN) as an alternative accurate technique to determine the rate of environmental contamination which can be used to solve the model equation. The first network is to simulate the soil parameters which can be used as input data in the second suggested network, while the second network sim
... Show MoreIbuprofen is one of the most important members of NSAIDs, named aryl propionic acid derivative. Isatin (1H-indole-2,3-dione) is an important molecule of heterocyclic compounds that have many biological activities. This work illustrates the synthesis of new ibuprofen-isatin derivatives by connecting ibuprofen hydrazide with different isatin derivatives by a condensation reaction, followed by characterization by fourier-transform infrared spectroscopy (FTIR) and proton nuclear magnetic resonance (1H-NMR) spectroscopy. The anti-inflammatory activity was evaluated by using the egg-white induce edema method for all the synthesized compounds (5-8), the compounds 5 and 6 showed better anti-inflammatory activity than ibuprofen as a standard
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Three new hydrazone derivatives of Etodolac were synthesized and evaluated for their anti-inflammatory activity by using egg white induced paw edema method. All the synthesized target compounds were characterized by CHN- microanalysis, FT-IR spectroscopy, and 1HNMR analysis. The synthesis of the target (P1-P3) compounds was accomplished following multistep reaction procedures. The synthesized target compounds were found to be active in reducing paw edema thickness and their anti-inflammatory effect was comparable to that of the standard (Etodolac).
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A new series of morpholine derivative were prepared by reacting the morpholine with ethyl chloro acetate in the presence triethylamine as an catalyst and benzene as a solvent gave the ethyl morpholin-4-ylacetate reaction with hydrazine hydrate and ethanol as a solvent gave the 2-(morpholin-4-yl)acetohydrazide gave series of Schiff base were prepared by reacting 2-(morpholin-4- yl)acetohydrazide with different aromatic aldehydes and ketons . The new series of (3-9 )were synthesis by reaction of Schiff base (10-14) with chloroacetyl chloride, triethyl amine as an catalyst and 1,4dioxane as a solvent .The chemical structures of the synthesis compound were identified by spectral methods their [ IR ,1H-NMR and 13C-NMR ].The synthesised compoun
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Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab
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Abstract
The research aims to build a training program to develop some executive functions for kindergarten children. To achieve this goal, the two researchers built the program according to the following steps:
1. Determining the general objective of the program.
2. Determining the behavioral objectives of the program.
3. Determining the included content in the program.
4. Implementing the content of the activities of the program.
5. Evaluating the Program.
The program included (12) training activities, the training activities included several items: the title of the activity, the time of implementation of the activity, the general objective of the activity, the procedural behavioral objective, the means and tools u