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The Minimum Cost for the Vascular Network Using Linear Programming Based Its Path Graph
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As of late, humankind has experienced radiation issues either computerized tomography (CT) or X-rays. In this investigation, we endeavor to limit the effect of examination hardware. To do this the medical image is cropping (cut and zoom) then represented the vascular network as a graph such that each contraction as the vertices and the vessel represented as an edges, the area of the coagulation was processed already, in the current search the shortest distance to reach to the place of the blood vessel clot is computed

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Speech Signal Compression Using Wavelet And Linear Predictive Coding
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A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of th

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Publication Date
Thu Jun 30 2022
Journal Name
International Journal Of Drug Delivery Technology
Expression of Vascular Endothelial Growth Factor in the Placenta of Iraqi Women Complicated with Hypertensive Disorder
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During pregnancy, high blood pressure disorder is the most common medical complication in pregnancy. It is the foremost cause of maternal mortality and perinatal diseases. Vascular endothelial growth factor (VEGF) affects the growth of vascular endothelial cells, existence, and multiplying, which are known to be expressed in the human placenta. This study aimed to identify the expression VEGF in the placenta of hypertension and normotensive women. In this study, a cross-sectional study from november 2019 to February 2020. A total of 100 placentae involved 50 hypertensive cases and 50 normotensive groups were assessed. VEGF-A expression in two placentas groups was evaluated by immunohistochemistry techniques. Strong and moderate VEGF

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Publication Date
Wed Sep 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
The Efficacy of Polidocanol foam Sclerotherapy in Treatment of Infantile Hemangioma and Slow-Flow Vascular Malformation
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Background: Sclerotherapy is a simple treatment modality for treatment of infantile hemangioma and slow-flow vascular malformations; Polidocanol is a mild sclerosing agent that is traditionally used in treatment of varicose veins. This study aims to evaluate the effectiveness, treatment outcome, and complications of polidocanol foam sclerotherapy for infantile hemangioma and slow-flow vascular malformations. Materials and methods: Between March 2013 and December 2014, seventeen patients with infantile hemangioma and slow-flow vascular malformations treated with polidocanol 1% foam sclerotherapy. Foam was prepared by Tessari’s method. Injection performed under general or local anesthesia, injections were repeated (if necessary) on mon

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Publication Date
Thu Dec 30 2021
Journal Name
Iraqi Journal Of Science
Image Georeferencing using Artificial Neural Network Compared with Classical Methods
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Georeferencing process is one of the most important prerequisites for various geomatics applications; for example, photogrammetry, laser scan analysis, remotely sensing, spatial and descriptive data collection, and others. Georeferencing mostly involves the transformation of coordinates obtained from images that are inhomogeneous due to accuracy differences. The georeferencing depends on image resolution and accuracy level of measurements of reference points ground coordinates.  Accordingly, this study discusses the subject of coordinate’s transformation from the image to the global coordinates system (WGS84) to find a suitable method that provides more accurate results. In this study, the Artificial Neural Network (ANN) method wa

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Publication Date
Sun Jul 30 2023
Journal Name
Iraqi Journal Of Science
Automatic Diagnosis of Coronavirus Using Conditional Generative Adversarial Network (CGAN)
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     A global pandemic has emerged as a result of the widespread coronavirus disease (COVID-19). Deep learning (DL) techniques are used to diagnose COVID-19 based on many chest X-ray. Due to the scarcity of available X-ray images, the performance of DL for COVID-19 detection is lagging, underdeveloped, and suffering from overfitting. Overfitting happens when a network trains a function with an  incredibly high variance to represent the training data perfectly. Consequently, medical images lack the availability of large labeled datasets, and the annotation of medical images is expensive and time-consuming for experts. As the COVID-19 virus is an infectious disease, these datasets are scarce, and it is difficult to get large datasets

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Publication Date
Tue Jan 12 2016
Journal Name
Wireless Networks
Low communication cost (LCC) scheme for localizing mobile wireless sensor networks
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In recent years, the number of applications utilizing mobile wireless sensor networks (WSNs) has increased, with the intent of localization for the purposes of monitoring and obtaining data from hazardous areas. Location of the event is very critical in WSN, as sensing data is almost meaningless without the location information. In this paper, two Monte Carlo based localization schemes termed MCL and MSL* are studied. MCL obtains its location through anchor nodes whereas MSL* uses both anchor nodes and normal nodes. The use of normal nodes would increase accuracy and reduce dependency on anchor nodes, but increases communication costs. For this reason, we introduce a new approach called low communication cost schemes to reduce communication

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Publication Date
Thu Dec 01 2022
Journal Name
Neuroscience Informatics
Epileptic EEG activity detection for children using entropy-based biomarkers
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Publication Date
Sat Dec 02 2023
Journal Name
Journal Of Engineering
The Cost of Technology Transfer in Construction Companies (In Iraq)
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The construction sector is considered an important and influential pivot in the national economy of any country.  Nations are working to develop this sector, receiving modern and developed techniques. So, this sector can be a carrier or a receiver of modern technologies. The cost of technology transfer between the international companies that sponsor this sector is a matter of great importance, especially since different factors affect the need for this advanced technology. The cost of technology transfer in construction is related to multiple factors presented by Knowledge, equipment, plant, hardware and software. The lack of distinguishing and evaluating the direct and indirect costs in the construction sector during

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Evaluating the levels of Tumor Necrosis Factorα-, Interleukin-6 and Vascular endothelial growth factor in patients with Colorectal Cancer
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     Cytokines are polypeptides with several functions that are produced by a variety of bodily cells. They are clinically significant for illness diagnosis, treatment, and prevention. Interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) are the most important cytokines for cell division and proliferation. Vascular endothelial growth factor (VEGF) is produced in excess in mesenchymal, epithelial, and especially in tumor cells. In this study the serum levels of IL-6, TNF-α and VEGF were detected for 41 colorectal cancer patients and 41 healthy control group at Nanakaly Hospital by comparing their serum concentrations for patients paining from colorectal carcinoma (CRC) with those of the control subjects. The result shows a s

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Publication Date
Thu Jun 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Performance Improvement of Neural Network Based RLS Channel Estimators in MIMO-OFDM Systems
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The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

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