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Assessment Of Vascular And Lymphatic Vessels Density In Benign Vascular Lesions Using CD34 And D2-40 Immunohistochemical Markers
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Background: Vascular tumors and malformations, comprising a broad category of lesions often referred to as vascular anomalies. Hemangioma, represents a variety of vascular lesions (both malformations and tumor), while lobular capillary hemangioma is a common vascular lesion of the skin and mucous membranes that occurs mainly in children and young adults. Lymphangiomas are malformations of the lymphatic system. At the level of light microscopy the small lymphatics vessels may be similar to capillaries and sometimes are only tentatively identified by the nature of their contents or by immunohistochemical staining procedure. This study aimed to assess the vascular and lymphatic vessels density in benign vascular lesions using CD34 and D2-40 immunohistochemical markers. Materials and Methods: Twenty two formalin-fixed paraffin-embedded tissue blocks of Hemangioma/vascular malformation, thirty of lobular capillary hemangioma and another twenty of lymphangioma. Results: Lymphatic vessel density expressed by D2-40 immunomarker was found in all cases with mean (24.01±14.74) in lymphangioma ,for lobular capillary hemangioma it was (12.67±6.66) and for hemangioma was (9.77±6.82) where as the mean of microvessel density count measured by CD34 immunomarker was (49.87±31.97) for lobular capillary hemangioma , in hemangioma it was (37.42±23.40) and (25.90±12.23 ) for lymphangioma. Conclusions: All vascular lesions are a mixture of blood and lymphatic vessels with different proportions, hemangioma shows high percentage of blood vessels and lymphangioma shows high percentage of lymphatic vessels.

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
3-D OBJECT RECOGNITION USING MULTI-WAVELET AND NEURAL NETWORK
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This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as

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Publication Date
Mon Oct 10 2016
Journal Name
Iraqi Journal Of Science
Satellite image classification using KL-transformation and modified vector quantization
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In this work, satellite images classification for Al Chabaish marshes and the area surrounding district in (Dhi Qar) province for years 1990,2000 and 2015 using two software programming (MATLAB 7.11 and ERDAS imagine 2014) is presented. Proposed supervised classification method (Modified Vector Quantization) using MATLAB software and supervised classification method (Maximum likelihood Classifier) using ERDAS imagine have been used, in order to get most accurate results and compare these methods. The changes that taken place in year 2000 comparing with 1990 and in year 2015 comparing with 2000 are calculated. The results from classification indicated that water and vegetation are decreased, while barren land, alluvial soil and shallow water

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
Combined DWT and DCT Image Compression Using Sliding RLE Technique
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A number of compression schemes were put forward to achieve high compression factors with high image quality at a low computational time. In this paper, a combined transform coding scheme is proposed which is based on discrete wavelet (DWT) and discrete cosine (DCT) transforms with an added new enhancement method, which is the sliding run length encoding (SRLE) technique, to further improve compression. The advantages of the wavelet and the discrete cosine transforms were utilized to encode the image. This first step involves transforming the color components of the image from RGB to YUV planes to acquire the advantage of the existing spectral correlation and consequently gaining more compression. DWT is then applied to the Y, U and V col

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Publication Date
Thu Dec 15 2016
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Building Words Dictionary List Using Symbol Enumeration and Hashing Methodology
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Publication Date
Thu Jul 25 2019
Journal Name
Advances In Intelligent Systems And Computing
Solving Game Theory Problems Using Linear Programming and Genetic Algorithms
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Publication Date
Wed Jan 01 2025
Journal Name
Fusion: Practice And Applications
Enhanced EEG Signal Classification Using Machine Learning and Optimization Algorithm
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This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

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Publication Date
Mon Jun 04 2018
Journal Name
Baghdad Science Journal
Designing and Constructing the Strain Sensor Using Microbend Multimode Fiber
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The microbend sensor is designed to experience a light loss when force is applied to the sensor. The periodic microbends cause propagating light to couple into higher order modes, the existing higher order modes become unguided modes. Three models of deform cells are fabricated at (3, 5, 8) mm pitchand tested by using MMF and laser source at 850 nm. The maximum output power of (8, 5, 3)mm model is (3, 2.7, 2.55)nW respectively at applied force 5N and the minimum value is (1.9, 1.65, 1.5)nW respectively at 60N.The strain is calculated at different microbend cells ,and the best sensitivity of this sensor for cell 8mm is equal to 0.6nW/N.

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Publication Date
Tue Oct 01 2013
Journal Name
Sensors And Actuators A: Physical
Enhanced energy harvesting using multiple piezoelectric elements: Theory and experiments
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Publication Date
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effect of Using the Strategy of Roundhouse in the Achievement of Fourth Grade Students of Computer and Their Attitudes towards It
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The research aims to identify the effect of using the strategy of Roundhouse on the achievement of fourth-grade students of computer and their Attitudes towards it. The research sample consisted of (61) fourth-grade secondary school students distributed into the experimental group consisted of (31) students study computer according to the Roundhouse strategy, and the control group consisted of (30) students follow the traditional method. The researcher designed an achievement test consisting of (30) items of multiple choice. To measure the attitudes of students towards the computer, a questionnaire of (32) paragraphs with three alternatives was designed by the researcher. The results showed that there is a statistically significant diffe

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Intelligent Systems
An online COVID-19 self-assessment framework supported by IoMT technology
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Abstract<p>As COVID-19 pandemic continued to propagate, millions of lives are currently at risk especially elderly, people with chronic conditions and pregnant women. Iraq is one of the countries affected by the COVID-19 pandemic. Currently, in Iraq, there is a need for a self-assessment tool to be available in hand for people with COVID-19 concerns. Such a tool would guide people, after an automated assessment, to the right decision such as seeking medical advice, self-isolate, or testing for COVID-19. This study proposes an online COVID-19 self-assessment tool supported by the internet of medical things (IoMT) technology as a means to fight this pandemic and mitigate the burden on our nation</p> ... Show More
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