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Hybrid Techniques with Support Vector Machine for Improving Artifact Ultrasound Images

     The most common artifacts in ultrasound (US) imaging are reverberation and comet-tail. These are multiple reflection echoing the interface that causing them, and result in ghost echoes in the ultrasound image. A method to reduce these unwanted artifacts using a Otsu thresholding to find region of interest (reflection echoes) and output applied to median filter to remove noise. The developed method significantly reduced the magnitude of the reverberation and comet-tail artifacts. Support Vector Machine (SVM) algorithm is most suitable for hyperplane differentiate. For that, we use image enhancement, extraction of feature, region of interest, Otsu thresholding, and finally classification image datasets to normal or abnormal image. Because of the machine’s training for both types of images, the machine can now predict whether a new image is an abnormal image or a normal image. As a result, it reduced medical work for many checkups and other things. Our proposed method shows the correct classification result by more than 89%.

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Publication Date
Sat Mar 01 2008
Journal Name
Iraqi Journal Of Physics
Adaptive Smoothing Technique for Remotely Sensed Images Enhancement

Spatial and frequency domain techniques have been adopted in this search. mean
value filter, median filter, gaussian filter. And adaptive technique consists of
duplicated two filters (median and gaussian) to enhance the noisy image. Different
block size of the filter as well as the sholding value have been tried to perform the
enhancement process.

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Publication Date
Thu Dec 23 2021
Journal Name
Iraqi Journal Of Science
Noise Reduction, Enhancement and Classification for Sonar Images

    Ultrasound imaging has some problems with image properties output. These affects the specialist decision. Ultrasound noise type is the speckle noise which has a grainy pattern depending on the signal. There are two parts of this study. The first part is the enhancing of images with adaptive Weiner, Lee, Gamma and Frost filters with 3x3, 5x5, and 7x7 sliding windows. The evaluated process was achieved using signal to noise ratio (SNR), peak signal to noise ratio (PSNR), mean square error (MSE), and maximum difference (MD) criteria. The second part consists of simulating noise in a standard image (Lina image) by adding different percentage of speckle noise from 0.01 to 0.06. The supervised classification based minimum di

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
A Modified Advanced Encryption Standard for Color Images

     The widespread use of images, especially color images and rapid advancement of computer science, have led to an emphasis on securing these images and defending them against intruders. One of the most popular ways to protect images is to use encryption algorithms that convert data in a way that is not recognized by someone other than the intended user. The Advanced Encryption Standard algorithm (AES) is one of the most protected encryption algorithms. However, due to various types of theoretical and practical assaults, like a statistical attack, differential analysis, and brute force attack, its security is under attack.

In this paper, a modified AES coined as (M-AES) is proposed to improve the efficiency

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Publication Date
Tue Jan 25 2022
Journal Name
Iraqi Journal Of Science
A Modified Segmentation Approach for Real World Images Based on Edge Density Associated with Image Contrast Stretching

Segmentation of real world images considered as one of the most challenging tasks in the computer vision field due to several issues that associated with this kind of images such as high interference between object foreground and background, complicated objects and the pixels intensities of the object and background are almost similar in some cases. This research has introduced a modified adaptive segmentation process with image contrast stretching namely Gamma Stretching to improve the segmentation problem. The iterative segmentation process based on the proposed criteria has given the flexibility to the segmentation process in finding the suitable region of interest. As well as, the using of Gamma stretching will help in separating the

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Nurses' Knowledge About Chest Physiotherapy Techniques for Patients With Corona Virus Disease

Abstract

Objective(s): A descriptive study aimed to determine nurses' knowledge about chest physiotherapy techniques for patients with Corona virus disease and observe the relationship between nurses' knowledge and their socio-demographic characteristics.

Methodology: The study was directed in isolation units of Al- Hussein teaching hospitals in Thi-Qar, Iraq for the period from June 1st,  2022 to November 27th, 2022. Non- probability (purposively) sample comprised 41 nurses. A questionnaire was used for data collection and it consists of two parts: the first part comprises socio demographic features, the second part includes self- administered questionnaire sheet wa

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Advanced GIS-based Multi-Function Support System for Identifying the Best Route

Geographic Information Systems (GIS) are obtaining a significant role in handling strategic applications in which data are organized as records of multiple layers in a database. Furthermore, GIS provide multi-functions like data collection, analysis, and presentation. Geographic information systems have assured their competence in diverse fields of study via handling various problems for numerous applications. However, handling a large volume of data in the GIS remains an important issue. The biggest obstacle is designing a spatial decision-making framework focused on GIS that manages a broad range of specific data to achieve the right performance. It is very useful to support decision-makers by providing GIS-based decision support syste

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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Distinguishing Cartoons Images from Real –Life Images

Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Applying some hybrid models for modeling bivariate time series assuming different distributions for random error with a practical application

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

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Publication Date
Sun Apr 24 2022
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Duplex ultrasound surveillance for asymptomatic deep venous thrombosis after total knee joint replacement

Background: The prevalence of deep veins thrombosis, complicating total knee replacement in Asian countries, has not been fully appreciated in comparison to western countries as there are few studies on that. There is an important correlation between the evidence of deep veins thrombosis in the lower extremity and likelihood of   pulmonary embolism later one . Because of its noninvasive nature, duplex ultrasound has become one of the initial dependable modality for the cheek out of deep veins thrombosis after total knee replacement  . Therefore, this study was designed to evaluate the outcome of asymptomatic after total knee replacement by duplex ultrasound among Iraqi patients.

Methods: This

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Publication Date
Thu Nov 01 2018
Journal Name
International Journal Of Biomathematics
A non-conventional hybrid numerical approach with multi-dimensional random sampling for cocaine abuse in Spain

This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ

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