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VSM Based Models and Integration of Exact and Fuzzy Similarity For Improving Detection of External Textual Plagiarism admin June 29, 2019
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Publication Date
Mon Feb 08 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
AWN-similarity: Towards developing free open-source frameworks for measuring Arabic semantic similarity under Windows / Linux operating systems
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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Publication Date
Sun Apr 01 2018
Journal Name
Al–bahith Al–a'alami
Addressing the Palestinian Cause by Talk shows of Russia Today and Alhurra June 2014- May 2015
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The purpose of this analytical study is to showcase how Russia Today and U.S Alhurra channels addressed the Palestinian Cause between the periods of mid-2014 and mid-2015. In addition, the study aims to highlight the “significance levels” of the Palestinian Cause in both channels.
The study is based on a rigorous survey methodology adopted by the researcher and based on the content analysis of Russia Today’s “Panorama” talk show and Alhurra’s “Free Hour show”.
First level examination included the content analysis of 398 talk show episodes broadcasted by both channels during the period through which the study was conducted.
Second level examination featured a detailed analysis of 38 episodes covering Palestinian A

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
A Tri-Gene Ontology Migration Operator for Improving the Performance of Meta-heuristics in Complex Detection Problems
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      Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulate

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Publication Date
Mon Dec 01 2014
Journal Name
Advances In Engineering Software
System identification and control of robot manipulator based on fuzzy adaptive differential evolution algorithm
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Publication Date
Mon Feb 21 2022
Journal Name
Iraqi Journal For Computer Science And Mathematics
Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

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Publication Date
Sun Sep 15 2019
Journal Name
Route Education And Social Science Journal
The influence of textual and visual reading on EFL Iraqi students' comprehension
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Reading roles as the third skill in the range of English as a Foreign Language (EFL) learning. Although the capability of reading in both academic and non-academic texts is assessed on standardized tests, few of oral interpretation of written language excludes images from estimating literary knowledge. This paper highlights strategies of reading comprehension and visual literacy. It aims to investigate either textual or visual reading in EFL can make an impact on students' comprehension. The effective use of visuals changes instructing reading comprehension recently.The imagery-text model can affect developing reading comprehension and enhancing intellectual thinking. The study hypothesizes that there is no relationship between reading and

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
An Efficient Shrinkage Estimators For Generalized Inverse Rayleigh Distribution Based On Bounded And Series Stress-Strength Models
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Abstract<p>In this paper, we investigate two stress-strength models (Bounded and Series) in systems reliability based on Generalized Inverse Rayleigh distribution. To obtain some estimates of shrinkage estimators, Bayesian methods under informative and non-informative assumptions are used. For comparison of the presented methods, Monte Carlo simulations based on the Mean squared Error criteria are applied.</p>
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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials &amp; Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
Deep Learning Approach for Oil Pipeline Leakage Detection Using Image-Based Edge Detection Techniques
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Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

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