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Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Publication Date
Tue Sep 11 2018
Journal Name
Iraqi Journal Of Physics
Estimation of kidney tumor volume in CT images using medical image segmentation techniques
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Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Big-data Management using Map Reduce on Cloud: Case study, EEG Images' Data
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Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

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Publication Date
Wed Dec 23 2020
Journal Name
2020 International Conference On Advanced Science And Engineering (icoase)
A Comparative Study Using LZW with Wavelet or DCT for Compressing Color Images
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As a result of the significance of image compression in reducing the volume of data, the requirement for this compression permanently necessary; therefore, will be transferred more quickly using the communication channels and kept in less space in memory. In this study, an efficient compression system is suggested; it depends on using transform coding (Discrete Cosine Transform or bi-orthogonal (tap-9/7) wavelet transform) and LZW compression technique. The suggested scheme was applied to color and gray models then the transform coding is applied to decompose each color and gray sub-band individually. The quantization process is performed followed by LZW coding to compress the images. The suggested system was applied on a set of seven stand

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Publication Date
Tue Aug 15 2023
Journal Name
Al-academy
Digital technologies in the means of communication
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Modern digital technologies have affected the means of communication in terms of structure, function and methods of dealing with them, and the communication process has changed, becoming bilateral, reciprocal and interactive, after it was one-way and limited in circulation and the roles changed, so the receiver became the sender and reversed is correct, and the culture of the active user and the participant spread, and the communication process became continuous.
The international information network has provided new electronic channels in the media and communication that are not known and opened a new era for these means, which led to a trend towards digital media in an unprecedented way.
The new communication platforms are the re

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Means of Arguments in Bank's Annual Reports
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In line with the most recent trends in genre analysis (Swales, 1990; Bahatia,
1993) and discourse studies on business communication (Dudley-Evans and St.
John, 1998;Bargiela-Chiappini, F. and C. Nickerson, 1999, the article focuses on a
particular financial genre, Bank's Annual Reports (ARs). More in detail, in contrast
in widespread claim about the purely financial and informative nature of ARs,
addressing experts only, this paper aims at illustrating in accordance with Bexley
and Hynes (2003), and Burrough's (1986) considerations, that those reports
endeavour to promote the company image and to leave a positive impression on
readers. Generally speaking, companies communicate because they exist: they have
a na

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Publication Date
Thu Dec 01 2011
Journal Name
Engineering Analysis With Boundary Elements
Numerical solution of two-dimensional mixed problems with variable coefficients by the boundary-domain integral and integro-differential equation methods
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Publication Date
Tue Jun 01 2021
Journal Name
Political Sciences Journal
Violence and Extremism in Iraq: Approaches to Motives and Means of Confrontation
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     After the year 2003, Iraq went through multiple waves of violence and at different levels on the security, intellectual, political and social levels. Behind that stood several motives and incentives to enable violence that represented the first axis of research, the most important of which was the political motives that circulated an atmosphere that politics against society and transformed power into a field of political brutality against the individual and the group at once. There are also cultural, intellectual, media and economic motives such as weak cultural independence, poverty, marginalization, unemployment and want, and the absence of a media discourse that rejects violence but incites it, on the other ha

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Publication Date
Wed Apr 01 2015
Journal Name
2015 Annual Ieee Systems Conference (syscon) Proceedings
Automatic generation of fuzzy classification rules using granulation-based adaptive clustering
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Publication Date
Fri Sep 30 2016
Journal Name
Australian Journal Of Basic And Applied Sciences
Programming Exam Questions Classification Based On Bloom’s Taxonomy Using Grammatical Rule
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Publication Date
Mon Oct 01 2018
Journal Name
Iraqi Journal Of Physics
Classification of brain tumors using the multilayer perceptron artificial neural network
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Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect

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