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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
Sun Apr 03 2016
Journal Name
Journal Of Educational And Psychological Researches
The impact of the model and follows on the collection and Retention of fifth grade students (oiterary) in history
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The first chapter the importance of research and need for education scientists see that the roots of the use of a specimen Wheatley in learning and teaching back to Grayson Wheatley, one of the largest supporters of a modern construction, which lay the groundwork for the specimen stage and the form in which it is. That was attributed to him, often called his name called while some educators based learning strategy on the issue. He sees the learner in this model make him a meaningful understanding of problems during his progress, thereby acting with his colleagues to find solutions to them in small groups. He

        Borders Search: Search by students is determined by th

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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
Modified Elman Spike Neural Network for Identification and Control of Dynamic System
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Publication Date
Wed Jun 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Advanced Study of Promoted Pt /SAPO-11 Catalyst for Hydroisomerization of the n-Decane Model and Lube Oil
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SAPO-11 is synthesized from silicoaluminophosphate in the presence of di-n-propylamine as a template. The results show that the sample obtained has good crystallinity, 396m2/g BET surface area, and 0.35 cm3/g pore volume. The hydroisomerization activity of (0.25)Pt (1)Zr (0.5)W/SAPO-11 catalyst was determined using n-decane and base oil. All hydroisomerization experiments of n-decane were achieved at a fixed bed plug flow reactor at a temperature range of 200-275°C and  LHSV 0.5-2h-1.  The results show that the n-decane conversion increases with increasing temperature and decreasing LHSV, the maximum conversion of 66.7 % was achieved at temperature 275°C and LHSV of 0.5 h-1. Meanwhile, the same catalyst was used to improve base oil spec

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Using system dynamics model and the statistical indicators for Road Map of "Green government departments" project In Iraq
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Abstract                                                         

The issue of the protection of the environment is a shared responsibility between several destinations and sectors, and constitutes a main subject in which they can achieve sustainable development. In the sectors of government programs can be set up towards the establishment of the government sector to the green environment, so to be the implementati

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Publication Date
Wed Jun 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Advanced Study of Promoted Pt /SAPO-11 Catalyst for Hydroisomerization of the n-Decane Model and Lube Oil
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   SAPO-11 is synthesized from silicoaluminophosphate in the presence of di-n-propylamine as a template. The results show that the sample obtained has good crystallinity, 396m2/g BET surface area, and 0.35 cm3/g pore volume. The hydroisomerization activity of (0.25)Pt (1)Zr (0.5)W/SAPO-11 catalyst was determined using n-decane and base oil. All hydroisomerization experiments of n-decane were achieved at a fixed bed plug flow reactor at a temperature range of 200-275°C and  LHSV 0.5-2h-1.  The results show that the n-decane conversion increases with increasing temperature and decreasing LHSV, the maximum conversion of 66.7 % was achieved at temperature 275°C and LHSV of 0.5 h-1

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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of weighted estimated method and proposed method (BEMW) for estimation of semi-parametric model under incomplete data
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Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Robust Two-Step Estimation and Approximation Local Polynomial Kernel For Time-Varying Coefficient Model With Balance Longitudinal Data
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      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
On Training Of Feed Forward Neural Networks
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In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Using Markov chains to forecast the exports of Iraqi crude oil
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       In this paper, the topic of forecasting the changes in the value of Iraqi crude oil exports for the period from 2019 to 2025, using the Markov transitional series based on the data of the time series for the period from January 2011 to November 2018, is real data obtained from the published data of the Central Agency Of the Iraqi statistics and the Iraqi Ministry of Oil that the results reached indicate stability in the value of crude oil exports according to the data analyzed and listed in the annex to the research.

Keywords: Using Markov chains

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Publication Date
Fri Dec 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A comparative study of Gaussian mixture algorithm and K-means algorithm for efficient energy clustering in MWSN
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Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener

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