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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 time. Here, we adopt a new perspective towards detecting the evolution of community structures. The proposed method realizes the decomposition of the problem into three essential components; searching in: intra-community connections, inter-community connections, and community evolution. A multi-objective optimization problem is defined to account for the different intra and inter community structures. Further, we formulate the community evolution problem as a Hidden Markov Model in an attempt to dexterously track the most likely sequence of communities. Then the new model, called Hidden Markov Model-based Multi-Objective evolutionary algorithm for Dynamic Community Detection (HMM-MODCD), uses a multi-objective evolutionary algorithm and Viterbi algorithm for formulating objective functions and providing temporal smoothness over time for clustering dynamic networks. The performance of the proposed algorithm is evaluated on synthetic and real-world dynamic networks and compared against several state-of-the-art algorithms. The results clearly demonstrate the effectiveness of the proposed algorithm to outperform other algorithms.

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Publication Date
Tue Jun 03 2025
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Comparison of some artificial neural networks for graduate students
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Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Southwest Jiaotong University
Image Segmentation for Skin Detection
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Human skin detection, which usually performed before image processing, is the method of discovering skin-colored pixels and regions that may be of human faces or limbs in videos or photos. Many computer vision approaches have been developed for skin detection. A skin detector usually transforms a given pixel into a suitable color space and then uses a skin classifier to mark the pixel as a skin or a non-skin pixel. A skin classifier explains the decision boundary of the class of a skin color in the color space based on skin-colored pixels. The purpose of this research is to build a skin detection system that will distinguish between skin and non-skin pixels in colored still pictures. This performed by introducing a metric that measu

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Publication Date
Wed May 01 2024
Journal Name
Scientific Visualization
Shadow Detection and Elimination for Robot and Machine Vision Applications
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Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Cam Dynamic Synthesis
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The paper presents an original method to make the geometric synthesis of the rotary cam and translated tappet with roll. Classical method uses to the geometric synthesis and the reduced tappet velocity, and in this mode the geometric classic method become a geometric and kinematic synthesis method. The new geometric synthesis method uses just the geometric parameters (without velocities), but one utilizes and a condition to realize at the tapped the velocities predicted by the tapped movement laws imposed by the cam profile. Then, it makes the dynamic analyze for the imposed cam profile, and one modify the cam profile geometric parameters to determine a good dynamic response (functionality). In this mode it realizes the dynamic synthesis

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Publication Date
Sun Nov 15 2020
Journal Name
Journal Of Petroleum Research And Studies
Reservoir Model and Production Strategy of Mishrif Reservoir-Nasryia Oil Field Southern Iraq
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Nasryia oil field is located about 38 Km to the north-west of Nasryia city. The field was discovered in 1975 after doing seismic by Iraqi national oil company. Mishrif formation is a carbonate rock (Limestone and Dolomite) and its thickness reach to 170m. The main reservoir is the lower Mishrif (MB) layer which has medium permeability (3.5-100) md and good porosity (10-25) %. Form well logging interpretation, it has been confirmed the rock type of Mishrif formation as carbonate rock. A ten meter shale layer is separating the MA from MB layer. Environmental corrections had been applied on well logs to use the corrected one in the analysis. The combination of Neutron-Density porosity has been chosen for interpretation as it is c

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Publication Date
Thu Nov 01 2012
Journal Name
Iraqi Journal Of Science
THE EVOLUTION OF PLANETARY NEBULAE(PN) AND FADING TIME ACCORDING TO SYNTHETIC MODEL
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Abstract Planetary nebulae (PN) represents the short phase in the life of stars with masses (0.89-7) M☉. Several physical processes taking place during the red giant phase of low and intermediates-mass stars. These processes include :1) The regular (early ) wind and the envelope ejection, 2) The thermal pulses during Asymptotic Giant Branch (AGB ) phase. In this paper it is briefly discussed how such processes affect the mass range of Planetary Nebulae(PN) nuclei(core) and their evolution, and the PN life time, and fading time for the masses which adopted. The Synthetic model is adopted. The envelope mass of star (MeN ) and transition time (ttr) calculated respectively for the parameter (MeR =1.5,2, 3×10-3 M☉). Another time scale is o

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Publication Date
Mon Oct 01 2018
Journal Name
Al–bahith Al–a'alami
Electronic media and social issues in Algeria The podcast technique is a model
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This study we have made a subject of fanny podcast in electronic media, as a new way to express different issues by the public, This study focuses started on how to address social issues in Alegria by ANAS TINA vidéo on the youtube network , you are to know the trends of young amateur about the various issues dealt with as well as the most important methods used to convince browsers.
The researcher used the survey method based on studying 10 episodes videos of blogger ANAS TINA.
The result of the study found that the most important issues are the abduction of children, teaching in Algeria; women in Algeria, The negative aspects of the issues addressed have been established in order to direct public opinion and awareness of ph

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Publication Date
Mon Aug 21 2023
Journal Name
Communications In Mathematical Biology And Neuroscience
Delay in eco-epidemiological prey-predator model with predation fear and hunting cooperation
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It is recognized that organisms live and interact in groups, exposing them to various elements like disease, fear, hunting cooperation, and others. As a result, in this paper, we adopted the construction of a mathematical model that describes the interaction of the prey with the predator when there is an infectious disease, as well as the predator community's characteristic of cooperation in hunting, which generates great fear in the prey community. Furthermore, the presence of an incubation period for the disease provides a delay in disease transmission from diseased predators to healthy predators. This research aims to examine the proposed mathematical model's solution behavior to better understand these elements' impact on an eco-epidemi

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Engineering
Toward Improving BIM Acceptance in FM: A Conceptual Model Integrating TTF and TAM
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Substantial research has been performed on Building Information Modeling (BIM) in various topics, for instance, the use and benefit of BIM in design, construction, sustainable environment building, and Facility assets over the past several years. Although there are various studies on these topics, Building Information Modeling (BIM) awareness through facilities management is still relatively poor. The researcher's interest is increased in BIM study is based heavily upon the perception that it can facilitate the exchange and reuse of information during various project phases. This property and others can be used in the Iraqi Construction industry to motivate the government to eliminate the change resistance to use innovat

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Publication Date
Tue Feb 27 2024
Journal Name
Mathematical Modelling Of Engineering Problems
Dynamics of a Fractional-Order Prey-Predator Model with Fear Effect and Harvesting
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