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A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions

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Publication Date
Tue Aug 31 2021
Journal Name
Iraqi Journal Of Science
Medical Image Classification for Coronavirus Disease (COVID-19) Using Convolutional Neural Networks

     The coronavirus is a family of viruses that cause different dangerous diseases that lead to death. Two types of this virus have been previously found: SARS-CoV, which causes a severe respiratory syndrome, and MERS-CoV, which causes a respiratory syndrome in the Middle East. The latest coronavirus, originated in the Chinese city of Wuhan, is known as the COVID-19 pandemic. It is a new kind of coronavirus that can harm people and was first discovered in Dec. 2019. According to the statistics of the World Health Organization (WHO), the number of people infected with this serious disease has reached more than seven million people from all over the world. In Iraq, the number of people infected has reached more than tw

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Publication Date
Sun Jul 01 2018
Journal Name
Ieee Transactions On Intelligent Transportation Systems
Real-Time Intersection-Based Segment Aware Routing Algorithm for Urban Vehicular Networks

High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

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Publication Date
Fri Jan 01 2016
Journal Name
Advances In Computing
A New Abnormality Detection Approach for T1-Weighted Magnetic Resonance Imaging Brain Slices Using Three Planes

Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co

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Publication Date
Wed Dec 11 2019
Journal Name
Journal Of The College Of Education For Women
Turkish Policy Towards Africa in the Era of the Justice and Development Party

Turkish policy towards Africa witnessed important developments over time that began before the Ottoman era and then developed during the Ottoman era when the Ottoman state played an important role in maintaining security by confronting Portuguese interventions in North Africa and sending military aid. Thus, the Ottoman state was able to develop its policy towards Africa for important considerations based mainly on the employment of the religious factor and the spread of Islam for the African acceptance of the Ottomans in the African territories and thus, achieve economic, strategic and political motives. Later, these relations declined in the Republican era due to the weak political and economic potential of Turkey on the one hand and th

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Publication Date
Sat Jun 15 2024
Journal Name
Journal Of Legal Sciences
Scientific chairs of Iraqi universities and their role in achieving sustainable development goals

تهدف الدراسة إلى استعراض ظهور كراسي اليونسكو في الجامعات العراقية والأنشطة التي تم تنفيذها لتحقيق أهداف التنمية المستدامة، حيث تم إنشاء كل كرسي لتحقيق أحد هذه الأهداف التي تركت أثرها على بعض القطاعات التعليمية والاجتماعية ، وبالتالي تنبع أهمية الدراسة من الحاجة إلى الإشارة إلى إنشاء كراسي اليونسكو في الجامعات العراقية والأنشطة التي عززت إنشائها ونشاطها ومبادراتها المحلية والدولية, وكذلك تحديد ما حقق

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Publication Date
Sun Jan 27 2019
Journal Name
Journal Of The College Of Education For Women
Historical Paths of the Political Conflict in Iraq and its Development After 3002

Following the political development in Iraq Since 7112 exposed kind of political traditions about how to manage the conflicts that have different Iraqi powers .That what was clear since the formation of permanent government since in 7112 .
The case of conflict between political powers in administrating Iraq state and the withdrawal of American Forcesintroduces questions:
0-Is it possible that that the beginning of Iraq state building shall ease this conflict and peacemaking in the post-conflict period?
7- To what extent the Iraqi powerswas to manage their disputes in non-military like elections which was held in 7112?
2- What is the range of the extent of the political operation after the American withdrawal?
The important

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Publication Date
Sat Jun 27 2020
Journal Name
Iraqi Journal Of Science
The Performance Differences between Using Recurrent Neural Networks and Feedforward Neural Network in Sentiment Analysis Problem

 With the spread use of internet, especially the web of social media, an unusual quantity of information is found that includes a number of study fields such as psychology, entertainment, sociology, business, news, politics, and other cultural fields of nations. Data mining methodologies that deal with social media allows producing enjoyable scene on the human behaviour and interaction. This paper demonstrates the application and precision of sentiment analysis using traditional feedforward and two of recurrent neural networks (gated recurrent unit (GRU) and long short term memory (LSTM)) to find the differences between them. In order to test the system’s performance, a set of tests is applied on two public datasets. The firs

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Publication Date
Fri Feb 17 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Deploying Facial Segmentation Landmarks for Deepfake Detection

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

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Publication Date
Mon Jan 10 2022
Journal Name
Iraqi Journal Of Science
Genetic Algorithm based Clustering for Intrusion Detection

Clustering algorithms have recently gained attention in the related literature since
they can help current intrusion detection systems in several aspects. This paper
proposes genetic algorithm (GA) based clustering, serving to distinguish patterns
incoming from network traffic packets into normal and attack. Two GA based
clustering models for solving intrusion detection problem are introduced. The first
model coined as handles numeric features of the network packet, whereas
the second one coined as concerns all features of the network packet.
Moreover, a new mutation operator directed for binary and symbolic features is
proposed. The basic concept of proposed mutation operator depends on the most
frequent value

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Publication Date
Mon Feb 01 2021
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Differential evolution detection models for SMS spam

With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative

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