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bsj-2553
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

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Publication Date
Sun Jul 25 2021
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
A Survey paper on Lossy Audio Compression Methods
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During the two last decades ago, audio compression becomes the topic of many types of research due to the importance of this field which reflecting on the storage capacity and the transmission requirement. The rapid development of the computer industry increases the demand for audio data with high quality and accordingly, there is great importance for the development of audio compression technologies, lossy and lossless are the two categories of compression. This paper aims to review the techniques of the lossy audio compression methods, summarize the importance and the uses of each method.

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Content Based Image Retrieval (CBIR) by Statistical Methods
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            An image retrieval system is a computer system for browsing, looking and recovering pictures from a huge database of advanced pictures. The objective of Content-Based Image Retrieval (CBIR) methods is essentially to extract, from large (image) databases, a specified number of images similar in visual and semantic content to a so-called query image. The researchers were developing a new mechanism to retrieval systems which is mainly based on two procedures. The first procedure relies on extract the statistical feature of both original, traditional image by using the histogram and statistical characteristics (mean, standard deviation). The second procedure relies on the T-

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Publication Date
Tue Nov 18 2025
Journal Name
Al–bahith Al–a'alami
Convincing methods in designing infographic content analytical study
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The research aims to reveal the recent trends used in providing information and to know the persuasive methods used in designing the content of the infographic as well as the nature of persuasive design methods and the topics presented by the infographic in the research sample.   The researcher used the survey method, specifically the survey, by using the content analysis method to analyze the infographic material from the sample selected from the press and news sites that are the subject of the research, based on the method of what was said? How was it said? The researcher relied on the intentional sample, and this sample depends on the researcher selecting the vocabulary of the sample based on experiences and evaluating the c

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Publication Date
Mon Jan 01 2018
Journal Name
Asian Journal Of Ournal Of Chemistry
Extraction of Ocimum basillicum Oil by Solvents Methods
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The extraction of Basil oil from Iraqi Ocimum basillicum leaves using n-hexane and petroleum ether as organic solvents were studied and compared. The concentration of oil has been determined in a variety of extraction temperatures and agitation speed. The solvent to solid ratio effect has been studied in order to evaluate the concentration of Ocimum basillicum oil. The optimum experimental conditions for the oil extraction were established as follows: n-hexane as organic solvent, 60 °C extraction temperature, 300 rpm agitation speed and 40:1mL:g amount of solvent to solid ratio.

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Physics: Conference Series
Bayesian Computational Methods of the Logistic Regression Model
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Abstract<p>In this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.</p>
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Publication Date
Sun Jun 26 2016
Journal Name
E-marefa
Evolution level of Iraqi journalists residing in Jordan of covering the political and economic reforms in Iraq by the Iraqi satellite TV stations
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هدفت الدراسة إلى التعرف على مستوى تقييم الإعلاميين العراقيين المقيمين في الأردن لتغطية الإصلاحات السياسية و الاقتصادية في العراق من قبل الفضائيات العراقية. و هدفت كذلك إلى التعرف على الف

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Publication Date
Tue Nov 18 2025
Journal Name
Al–bahith Al–a'alami
Preferences of the Iraqi Public towards Arab News Channels Programs and Materials (Al Jazeera, Al Arabiya, Al Ekhbariya Satellite Channels: a field Study)
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Broadcasting across satellites has become an important media phenomenon and largely available for watchers. As the receiver can see the events at the very moment and at any spot in the world. This study aims to discover the degree of the extent of exposure of Iraqi people to the news broadcasting satellites in Arabic language, (Al Jazeera, Al Arabiya, Al Ekhbariya Satellite Channels) as one of the media that serves the public; and to discover the range of these Satellite Channels in covering the local Iraqi situation in different sides and aspects; and to know the significance of the Iraqi people in watching those news programmers; and state the motives behind the Iraqi public's dependence on these channels.

The

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Publication Date
Fri Feb 01 2019
Journal Name
Iraqi Journal Of Information &amp; Communications Technology
Evaluation of DDoS attacks Detection in a New Intrusion Dataset Based on Classification Algorithms
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Intrusion detection system is an imperative role in increasing security and decreasing the harm of the computer security system and information system when using of network. It observes different events in a network or system to decide occurring an intrusion or not and it is used to make strategic decision, security purposes and analyzing directions. This paper describes host based intrusion detection system architecture for DDoS attack, which intelligently detects the intrusion periodically and dynamically by evaluating the intruder group respective to the present node with its neighbors. We analyze a dependable dataset named CICIDS 2017 that contains benign and DDoS attack network flows, which meets certifiable criteria and is ope

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Publication Date
Wed Sep 16 2020
Journal Name
Al-kindy College Medical Journal
The importance of anatomical zonal classification in the early management of penetrating neck injuries
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Background: Penetrating neck injuries are common problem in our country due to increasing violence, terrorist bombing and military operations.
These injuries are potentially life threating and need great attention and proper management.
Objective: The aim of this study is to focus on the importance of anatomical zonal classification of the neck in the management of penetrating injuries of the visceral compartment of the Neck.
Methods :70 patients with various injuries who were managed at causality unit and Otolaryngology department in Al-Kindy Teaching Hospital during aperiod from January 1st 2015 to October 31st 2015.
The study carried on those patient depending on proper clinical examination and their urgent management.

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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