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The Use of Gradient Based Features for Woven Fabric Images Classification
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Publication Date
Fri Feb 01 2019
Journal Name
Iraqi Journal Of Information & 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
Fri May 01 2015
Journal Name
Journal Of Engineering
On Gradient Descent Localization in 3-D Wireless Sensor Networks
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Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo

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Publication Date
Tue Apr 30 2024
Journal Name
International Journal On Technical And Physical Problems Of Engineering
Deep Learning Techniques For Skull Stripping of Brain MR Images
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Deep Learning Techniques For Skull Stripping of Brain MR Images

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Publication Date
Sat Jul 06 2024
Journal Name
Multimedia Tools And Applications
Text classification based on optimization feature selection methods: a review and future directions
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A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

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Publication Date
Tue Sep 10 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A classification model on tumor cancer disease based mutual information and firefly algorithm
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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Sat Feb 02 2019
Journal Name
Journal Of The College Of Education For Women
The Technique Features of the 1990s Prose Poem in Iraq: The Technique Features of the 1990s Prose Poem in Iraq
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Abstract:
The prose poem of the 1990s is considered one of the important
contributions of the Iraqi poetic scene. The poem found a position in the Iraqi
poetry because of the favor of a group of youth poets who lefty clear traces.
Their linguistic techniques often violate the domain o9f language, significance
and image.
The poems of those youth poets moved the verse towards reality to
drink from its abundant springs in order to stand on a rigid ground. Their
linguistic traces are characterized by paradox and astonishment that are used
by the poet to construct his poem.

The paradox was considered an ideal means for constructing a
poem by some of them. The poem moved towards definitions and these
de

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Publication Date
Tue Jan 23 2018
Journal Name
Suleyman Demİrel University
ANALYZING POSTGRADUATE STUDENTS' USE OF PRAGMATIC FEATURES AND ARGUMENTATION IN THESIS WRITING: A CORPUS-BASED STUDY تحليل استخدام طلبة الدراسات العليا للسمات التداولية و الحجج في كتابة الرسائل العلمية : دراسة تعتمد تحليل البيانات المحوسبة
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This study addresses the issue of academic writing in English by comparing pragmatic argumentation in the writing of 40 graduate students studying at Iraqi universities (SSIU) with the writing of 40 graduate students studying at American universities (SSAU). In these 80 theses, six selected aspects of academic writing were analyzed: (a) paragraph structure, (b) length and construction of sentences, (c) organization of information in sentences, (d) vocabulary, (e) topic sentences, and (f) discourse markers. This study seeks to go beyond the traditional and often onedimensional analysis of pragmatics of argumentation in English academic writing to distinguish and describe different aspects of academic writing and their results when used by EF

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Publication Date
Tue Apr 02 2024
Journal Name
Advances In Systems Science And Applications
A New Face Swap Detection Technique for Digital Images
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge
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Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

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