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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 22 2021
Journal Name
Expert Systems
Hybrid intelligent technology for plant health using the fusion of evolutionary optimization and deep neural networks
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Publication Date
Mon Jun 09 2025
Journal Name
Intelligent Decision Technologies
Safety assessment model for DoS attacks detection in wireless communication and network OS environments
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Wireless networks and communications have witnessed tremendous development and growth in recent periods and up until now, as there is a group of diverse networks such as the well-known wireless communication networks and others that are not linked to an infrastructure such as telephone networks, sensors and wireless networks, especially in important applications that work to send and receive important data and information in relatively unsafe environments, cybersecurity technologies pose an important challenge in protecting unsafe networks in terms of their impact on reducing crime. Detecting hacking in electronic networks and penetration testing. Therefore, these environments must be monitored and protected from hacking and malicio

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Publication Date
Wed Feb 16 2022
Journal Name
Journal Of Economics And Administrative Sciences
Solving Resource Allocation Model by Using Dynamic Optimization Technique for Al-Raji Group Companies for Soft Drinks and Juices
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In this paper, the problem of resource allocation at Al-Raji Company for soft drinks and juices was studied. The company produces several types of tasks to produce juices and soft drinks, which need machines to accomplish these tasks, as it has 6 machines that want to allocate to 4 different tasks to accomplish these tasks. The machines assigned to each task are subject to failure, as these machines are repaired to participate again in the production process. From past records of the company, the probability of failure machines at each task was calculated depending on company data information. Also, the time required for each machine to complete each task was recorded. The aim of this paper is to determine the minimum expected ti

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Hiding Techniques for Dynamic Encryption Text based on Corner Point
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Hiding technique for dynamic encryption text using encoding table and symmetric encryption method (AES algorithm) is presented in this paper. The encoding table is generated dynamically from MSB of the cover image points that used as the first phase of encryption. The Harris corner point algorithm is applied on cover image to generate the corner points which are used to generate dynamic AES key to second phase of text encryption. The embedded process in the LSB for the image pixels except the Harris corner points for more robust. Experimental results have demonstrated that the proposed scheme have embedding quality, error-free text recovery, and high value in PSNR.

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Publication Date
Wed Mar 01 2023
Journal Name
Journal Of Engineering
A An Authentication and Access Control Model for Healthcare based Cloud Services
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Electronic Health Record (EHR) systems are used as an efficient and effective method of exchanging patients’ health information with doctors and other key stakeholders in the health sector to obtain improved patient treatment decisions and diagnoses. As a result, questions regarding the security of sensitive user data are highlighted. To encourage people to move their sensitive health records to cloud networks, a secure authentication and access control mechanism that protects users’ data should be established. Furthermore, authentication and access control schemes are essential in the protection of health data, as numerous responsibilities exist to ensure security and privacy in a network. So, the main goal of our s

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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Stability of Back Propagation Training Algorithm for Neural Networks
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In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

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Publication Date
Tue Nov 27 2018
Journal Name
The Iraqi Geological Journal
CHRONOSTRATIGRAPHICALLY BASED RESERVOIR MODEL FOR CENOMANIAN CARBONATES, SOUTHEASTERN IRAQ OILFIELDS
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The Cenomanian – Turronian sedimentary succession in the south Iraq oil fields, including Ahmadi, Rumaila, Mishrif and Khasib formations have undergone into high-resolution reservoir-scale genetic sequence stratigraphic analysis. Some oil-wells from Majnoon and West-Qurna oil fields were selected as a representative case for the regional sequence stratigraphic analysis. The south Iraqi Albian – Cenomanian – Turronian succession of 2nd-order depositional super-sequence has been analyzed based on the Arabian Plate chronosequence stratigraphic context, properly distinguished by three main chrono-markers (The maximum flooding surface, MFS-K100 of the upper shale member of Nahr Umr Formation, MFS-K140 of the upper Mishrif carbonate

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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Dynamic Routing Method over Hybrid SDN for Flying Ad Hoc Networks
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Due to the high mobility and dynamic topology of the FANET network, maintaining communication links between UAVs is a challenging task. The topology of these networks is more dynamic than traditional mobile networks, which raises challenges for the routing protocol. The existing routing protocols for these networks partly fail to detect network topology changes. Few methods have recently been proposed to overcome this problem due to the rapid changes of network topology. We try to solve this problem by designing a new dynamic routing method for a group of UAVs using Hybrid SDN technology (SDN and a distributed routing protocol) with a highly dynamic topology. Comparison of the proposed method performance and two other algorithms is simula

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Genetic Algorithm Optimization Model for Central Marches Restoration Flows with Different Water Quality Scenarios
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A Genetic Algorithm optimization model is used in this study to find the optimum flow values of the Tigris river branches near Ammara city, which their water is to be used for central marshes restoration after mixing in Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim of this model is to enhance the water quality in Maissan River, hence provide acceptable water quality for marsh restoration. The model is applied for different water quality change scenarios ,i.e. , 10%,20% increase in EC,TDS and BOD. The model output are the optimum flow values for the three rivers while, the input data are monthly flows(1994-2011),monthly water requirements and water quality parameters (EC, TDS, BOD, DO and

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Publication Date
Wed Sep 05 2007
Journal Name
Neural Network World
A canonical generic algorithm for likelihood estimator of first order moving average model parameter
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The increasing availability of computing power in the past two decades has been use to develop new techniques for optimizing solution of estimation problem. Today's computational capacity and the widespread availability of computers have enabled development of new generation of intelligent computing techniques, such as our interest algorithm, this paper presents one of new class of stochastic search algorithm (known as Canonical Genetic' Algorithm ‘CGA’) for optimizing the maximum likelihood function strategy is composed of three main steps: recombination, mutation, and selection. The experimental design is based on simulating the CGA with different values of are compared with those of moment method. Based on MSE value obtained from bot

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