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A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any intense interest to reflect the domain knowledge. Moreover, all the published reviews did not make any direct effort to link heuristic and metaheuristic based community detection approaches, rather, they simply state them separately. The review introduced in this paper attempts to address this issue. Mainly, we review the main heuristic and metaheuristic based community detection algorithms. Then, we introduce two new taxonomies for community detection algorithms: hybrid metaheuristic and hyper heuristic that can serve as common grounds for designing a collection of new and more effective MCD algorithms. To this end, we introduce four new systematic frameworks integrating both heuristic and metaheuristic algorithms, illustrating the possible issues that would fuel the desire for researchers to direct their future interest towards developing more effective community detection instances from the context of these frameworks.

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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
Simple 2D chaotic remapping scheme for securing optical communication networks
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In this work, a simple and new method is proposed to simultaneously improve the physical layer security and the transmission performance of the optical orthogonal frequency division multiplexing system, by combining orthogonal frequency division multiplexing technique with chaotic theory principles. In the system, a 2-D chaotic map is employed. The introduced system replaces complex operations such as matrix multiplication with simple operations such as multiplexing and inverting. The system performance in terms of bit error rate (BER) and peak to average ratio (PAPR) is enhanced. The system is simulated using Optisystem15 with a MATLAB2016 and for different constellations. The simulation results showed that the  BE

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Publication Date
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Lightweight route adjustment strategy for mobile sink wireless sensor networks
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<span>As a result of numerous applications and low installation costs, wireless sensor networks (WSNs) have expanded excessively. The main concern in the WSN environment is to lower energy consumption amidst nodes while preserving an acceptable level of service quality. Using multi-mobile sinks to reduce the nodes' energy consumption have been considered as an efficient strategy. In such networks, the dynamic network topology created by the sinks mobility makes it a challenging task to deliver the data to the sinks. Thus, in order to provide efficient data dissemination, the sensor nodes will have to readjust the routes to the current position of the mobile sinks. The route re-adjustment process could result in a significant m

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Publication Date
Mon Apr 20 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
A Robust Base-layer Design for Hierarchical IoT Intrusion Detection Using Hybrid Deep Learning
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The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines

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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
The Mental Disorder of mothers as a Mediating Variable Between Marital adjustment and Kindergarteners Development
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This current study aimed to explore the mediation effects of mother's mental health symptoms between marital adjustment and child development aspects. (666) participants of mothers and their children were the sample of the study. The researchers used the marital adjustment scale prepared by Manson, Morse, Lerner, Arthur, as well as, a package of tests for some aspects of growth Kindergarten children prepared by Kenawi and Mohamed (1999). In addition, theyemployed a list of modified symptoms (Symptom Checklist-90- Revised (SCL) -90-, prepared by Derogatis, Lipman and Lipogun & Cov (1976), The results of the current study showed there is a statistically significant relationship between marital adjustment and the symptoms of mental diso

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Publication Date
Tue Mar 05 2024
Journal Name
Journal Of Biotechnology Research Center,
A review of the Prevalence of Enterohemorrhagic E. coli in Iraq
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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Photoacoustic Imaging for Tumor Detection: An in vitro Simulation Study
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Photoacoustic is a unique imaging method that combines the absorption contrast of light or radio frequency waves with ultrasound resolution. When the deposition of this energy is sufficiently short, a thermo-elastic expansion takes place whereby acoustic waves are generated. These waves can be recorded and stored to construct an image. This work presents experimental procedure of laser photoacoustic two dimensional imaging to detect tumor embedded within normal tissue. The experimental work is accomplished using phantoms that are sandwiched from fish heart or blood sac (simulating a tumor) 1-14mm mean diameter embedded within chicken breast to simulate a real tissue. Nd: YAG laser of 1.064μm and 532nm wavelengths, 10ns pulse duration, 4

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Publication Date
Wed Mar 01 2023
Journal Name
Iraqi Journal Of Physics
Design and Construction of a Dust Detection System using Infrared Laser: The Case of Dust Storms in Baghdad in the Summer 2022
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Iraq suffers from serious pollution with harmful particles that have important direct and indirect effects on human activities and human health. In this research, a system for detecting pollutants in the air was designed and manufactured using infrared laser technology. This system was used to detect the presence of pollutants in the dust storms that swept the city of Baghdad which could have a negative impact on human health and living organisms.

The designed detection system based on the use of infrared laser (IR) with a wavelength of 1064 nm was used for the purposes of detecting pollutants based on the scattering of the laser beam from these pollutants. The system was aligned to obtain the best signal for the scattered rays, w

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Publication Date
Sun Jan 01 2017
Journal Name
Ursus
Community composition of Ixodid ticks parasitizing American black bears in Missouri, USA
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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Use Of Artificial Neural Networks In Developing The Role Of Auditor In Discovering Fundamental Errors: An Applied Research In General Company for Electrical Industries and Nasr General Company for Mechanical Industries
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Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi

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Publication Date
Tue Apr 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Industrial Policy and Development in Developing Countries (The Proponents and the Opponents
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This paper aims to discuss and analyse the role and importance of implementing industrial Policy to promote industry and enhance economic development in developing countries. The paper discusses the economic justifications for using industrial policy as well as the criticisms leveled against it, for this purpose it analyses the ideas of two different approaches to industrial policy. The first held by the neo-liberals in the USA , who oppose the use of industrial policy and emphasise the role of the market in attaining economic development. The second, represented by many economists who support the use of industrial policy to promote industry and accelerate economic development, they justify their stand by pointing to the negative

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