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
... Show MoreThe 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
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
... Show MoreThe 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
... Show MoreReading 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
... Show MoreIn 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.
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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