Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem. In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a local improvement operator to effectively discover community structure in the modular complex networks when employing the modularity density metric as a single-objective function. The framework of the proposed algorithm consists of three main steps: an initialization strategy, a movement strategy based on perturbation genetic operators, and an improvement operator. The key idea behind the improvement operator is to determine and reassign the complex network nodes that are located in the wrong communities if the majority of their topological links do not belong to their current communities, making it appear that these nodes belong to another community. The performance of the proposed algorithm has been tested and evaluated when applied to publicly-available modular complex networks generated using a flexible and simple benchmark generator. The experimental results showed the effectiveness of the suggested method in discovering community structure over modular networks of different complexities and sizes.
A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
... Show MoreThe paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme
... Show MoreBackground: Many types of instruments and techniques are used in the instrumentation of the root canal system. These instruments and techniques may extrude debris beyond the apical foramen and may cause post-instrumentation complications. The aim of this study was to evaluate the amount of apically extruded debris resulted by using 4 types of nickel-titanium instruments (WaveOne, TRUShape 3D conforming files, Hyflex CM, and One Shape files) during endodontic instrumentation. Materials and methods: Forty freshly extracted human mandibular second premolar with straight canals and a single apex were collected for this study. All teeth were cut to similar lengths. Pre-weighted glass vials were used as collecting containers. Samples were randoml
... Show MoreAbstract:
Due to the importance of technology and the accompanying changes of the environment affecting companies that use the technology mainly in their work, especially as most companies live in an unstable dynamic environment, which motivated the researchers to choose the International Company for smart card (Keycard) as a field of research and find ways to them to face Those changes.
The problem of the study was "limited attention to the components of technological change", which included research and development, innovation and information technology, which had an impact on the design decisions of the process (process selection, cust
... Show MoreThis research deals with a part of our heritage and Arab culture, which is the poetry of contemporary Islamic poets, especially the poetry that was said in the mother in contemporary Islamic poetry, when extrapolating the offices of some contemporary Islamic poets found a clear presence of the mother, and during the search for the subject or its I found that the subject did not receive research and study, although the bureaus of contemporary Islamic poets included in it a huge amount of verses in which they stood at the mother Pharthua, and expressed their feelings and emotions towards them, and accordingly this research tagged (mother in contemporary Islamic poetry _ Dr Artistic models in models of contemporary Islamic poetry) to stand
... Show Moreمع ان افلاطون في الفصلين السابع والعاشر من جمهوريته يعري المسرح بوصفه عالما زائفا يعج بالأخيلة التي يتوجب على المرء ان ينبذها ويتمسك بعالم الحقيقة، الا إن هذا لا يعدم الأثر البالغ الذي تركتهُ أرائهُ على المسرح، قديمهُ وحديثهُ،تجربهً وتنظيرا .إن حكايته الإستعارية للكهف ،والتي تعد مسرحةً للأفكارِ، إن هي إلا وسيلة ينفذ من خلالها الى جوهر المسرح. لذا فان مسرحية ونظرية الكهف قد اصبحت حجر الزاوية في ما قد اص
... Show MoreThe present study investigated the use of pretreated fish bone (PTFB) as a new surface, natural waste and low-cost adsorbent for the adsorption of Methyl green (MG, as model toxic basic dye) from aqueous solutions. The functional groups and surface morphology of the untreated fish bone (FB) and pretreated fish bone were characterized using Fourier transform infrared (FTIR), scanning electron microscopy (SEM) and Energy dispersive X-ray spectroscopy (EDS),respectively. The effect of operating parameters including contact time, pH, adsorbent dose, temperature, and inorganic salt was evaluated. Langmuir, Freundlich and Temkin adsorption isotherm models were studied and the results showed that the adsorption of basic dye followed Freundlich iso
... Show MoreThe present study investigated the use of pretreated fish bone (PTFB) as a new surface, natural waste and low-cost adsorbent for the adsorption of Methyl green (MG, as model toxic basic dye) from aqueous solutions. The functional groups and surface morphology of the untreated fish bone (FB) and pretreated fish bone were characterized using Fourier transform infrared (FTIR), scanning electron microscopy (SEM) and Energy dispersive X-ray spectroscopy (EDS), respectively. The effect of operating parameters including contact time, pH, adsorbent dose, temperature, and inorganic salt was evaluated. Langmuir, Freundlich and Temkin adsorption isotherm models were studied and the results showe
Azo dyes like methyl orange (MO) are very toxic components due to their recalcitrant properties which makes their removal from wastewater of textile industries a significant issue. The present study aimed to study their removal by utilizing aluminum and Ni foam (NiF) as anodes besides Fe foam electrodes as cathodes in an electrocoagulation (EC) system. Primary experiments were conducted using two Al anodes, two NiF anodes, or Al-NiF anodes to predict their advantages and drawbacks. It was concluded that the Al-NiF anodes were very effective in removing MO dye without long time of treatment or Ni leaching at in the case of adopting the Al-Al or NiF-NiF anodes, respectively. The structure and surface morphology of the NiF electrode were inves
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