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Open Access Article
1 - using clustering in AODV routing protocol for vehicular ad-hoc networks on highway scenario
amin feyziVehicular Ad hoc networks are a subset of mobile Ad hoc networks in which vehicles are considered as network nodes. Their major difference is rapid mobility of nodes which causes the quick change of topology in this network. Quick changes in the topology of the network MoreVehicular Ad hoc networks are a subset of mobile Ad hoc networks in which vehicles are considered as network nodes. Their major difference is rapid mobility of nodes which causes the quick change of topology in this network. Quick changes in the topology of the network are considered as a big challenge For routing in these networks, routing protocols must be robust and reliable. AODV Routing protocol is one of the known routing protocols in vehicular ad hoc networks. There are also some problems in applying this routing protocol on the vehicular ad hoc networks. The number of control massages increases with increasing the scale of the network and the number of nodes . One way to reduce the overhead in AODV routing protocol is clustering the nodes of the network. In this paper , the modified K-means algorithm has been used for clustering the nodes and particle swarm optimization has been used for selecting cluster head. The results of the proposed method improved normalized routing load and the increase of the packet delivery rate compared to AODV routing protocol. Manuscript profile -
Open Access Article
2 - Optimal LO Selection in E-Learning Environment Using PSO Algorithm
gholamali montazerOne of the key issues in e-learning is to identify needs, educational behavior and learning speed of the learners and design a suitable curriculum commensurate to their abilities. This goal is achieved by identifying the learners’ different dimension of personality and MoreOne of the key issues in e-learning is to identify needs, educational behavior and learning speed of the learners and design a suitable curriculum commensurate to their abilities. This goal is achieved by identifying the learners’ different dimension of personality and ability and assigning suitable learning material to them according these features. In this paper, an intelligent tutoring system is proposed which optimizes the LO selection in e-learning environment. In order to evaluate the proposed method, the designed system has been used in a web-based instruction system in different conditions and the results of the "Academically success", "Satisfactory learning achievement" and "Time of the learners’ attendance" have been analyzed. The obtained results show a significant efficiency compared to other applied methods. Manuscript profile -
Open Access Article
3 - Using a Hybrid PSO-GA Method for Capacitor Placement in Distribution Systems
mohammadmahdi Varahram amir mohammadiIn this paper, we have proposed a new algorithm which combines PSO and GA in such a way that the new algorithm is more effective and efficient.The particle swarm optimization (PSO) algorithm has shown rapid convergence during the initial stages of a global search but ar MoreIn this paper, we have proposed a new algorithm which combines PSO and GA in such a way that the new algorithm is more effective and efficient.The particle swarm optimization (PSO) algorithm has shown rapid convergence during the initial stages of a global search but around global optimum, the search process will become very slow. On the other hand, genetic algorithm is very sensitive to the initial population. In fact, the random nature of the GA operators makes the algorithm sensitive to the initial population. This dependence to the initial population is in such a manner that the algorithm may not converge if the initial population is not well selected. This new algorithm can perform faster and does not depend on initial population and can find optimal solutions with acceptable accuracy. Optimal capacitor placement and sizing have been found using this hybrid PSO-GA algorithm. We have also found the optimal place and size of capacitors using GA and PSO separately and compared the results. Manuscript profile -
Open Access Article
4 - Application of clustering in AODV routing protocol for intercity networks on the highway scenario
amin feyzi Vahid Sattari-Naeini majid mohammadiIntercarous networks are a subset of mobile networks in which vehicles are considered as network nodes. The main difference with case mobile networks is the rapid mobility of nodes, which causes rapid topology change in this network It becomes. Rapid changes in network MoreIntercarous networks are a subset of mobile networks in which vehicles are considered as network nodes. The main difference with case mobile networks is the rapid mobility of nodes, which causes rapid topology change in this network It becomes. Rapid changes in network topology are a major challenge for routing, for routing in these networks, routing protocols must be robust and reliable. One of the well-known routing protocols in intercity networks is the AODV routing protocol. The application of this routing protocol on intercity networks also has problems that increase the number of control messages in the network by increasing the scale of the network and the number of nodes. One way to reduce overhead in the AODV protocol is to cluster network nodes. In this paper, the modified K-Means algorithm is used to cluster the nodes and the particle swarm algorithm is used to select the cluster head. The results of the proposed method improve the normal routing load and increase the packet delivery rate compared to the AODV routing protocol. Manuscript profile -
Open Access Article
5 - The Investigation of Ability to Degradation and Removal of Various Dyes Using Silver Colloidal Nanoparticles
Mohadeseh Tavakoli Fariba OstovarColors are one of the most important pollutants of water, and only one entry into the water can significantly reduce the quality of water. In addition, due to the synthetic origin and the presence of complex molecules in the structure of colors, the purification process MoreColors are one of the most important pollutants of water, and only one entry into the water can significantly reduce the quality of water. In addition, due to the synthetic origin and the presence of complex molecules in the structure of colors, the purification process is sometimes accompanied by some problems. Colloidal nanoparticles play an important role in technology, especially in the manufacture of glass and ceramics, and are used as a suitable method for cleaning pollutants in water and wastewater. In this study, a chemical regeneration method was used to synthesize colloidal silver nanoparticles. Then, to evaluate the efficiency of synthetic silver nanoparticles, several solutions of dye and pigments such as sulfur, azo, reactive, cationic and anionic dyes were prepared and synthetic material was used for degradation of different colors. Finally, the effect of this colloidal nanoparticle on each of them was studied and compared. The results showed that silver colloidal nanoparticles have the ability to degradation and removal of methyl orange and methyl red dyes from aqueous samples, and these nanoparticles can be used for treatment the water and wastewater containing these dyes. Manuscript profile -
Open Access Article
6 - Evaluation and comparison of some green methods for synthesis of silver nanoparticles
sepide hamedi seyed abbas shojaossadatiNowadays, there is an increasing need to develop high-yield, low cost, nontoxic, and eco-friendly procedures for synthesis of metallic nanoparticles. Therefore, the green synthesis methods become customary for synthesis of nanoparticles. Among metallic nanoparticles, na MoreNowadays, there is an increasing need to develop high-yield, low cost, nontoxic, and eco-friendly procedures for synthesis of metallic nanoparticles. Therefore, the green synthesis methods become customary for synthesis of nanoparticles. Among metallic nanoparticles, nanosilver has developed because of its therapeutic properties. So in this paper, polysaccharide, tollens and biological green methods were investigated. In polysaccharide and tollens methods, starch and β-D glucose were used as a satabilizer and reducer respectively. In biological method biomass and cell filtrate of the Fusarium oxysporum fungus were used for the synthesis of nanoparticles. SEM images and UV-visible absorbtion spectra of these procedures showed that the polysaccharide method produced smaller silver nanoparticles wih high productivity. The changes of NADH-dependant nitrate reductase enzyme activity was evaluated in growh duration by colorometric Harely method due to importance of this enzyme in extracellular synthesis of silver nanoparticles. Results showed that the changes of dry cell mass impact on the enzyme activity. Manuscript profile -
Open Access Article
7 - Evaluation of the Efficiency of Tallens, Polysaccharides and microbial Methods in Synthesis of Silver Nanoparticles
One of the important aspects of nanotechnology application is expanding sustainable and eco-friendly procedures for synthesis of metallic nanoparticles. Therefore, the green synthesis methods become customary for synthesis of nanoparticles. In this research, green polys MoreOne of the important aspects of nanotechnology application is expanding sustainable and eco-friendly procedures for synthesis of metallic nanoparticles. Therefore, the green synthesis methods become customary for synthesis of nanoparticles. In this research, green polysaccharide methods, modified polysaccharide, tollens and microbial methods were investigated. In polysaccharide and tollens methods, starch and β-D glucose were used as a satabilizer and reducer respectively. In biological method biomass and cell filtrate of the Fusarium oxysporum fungus were used for synthesis of nanoparticles. SEM images and UV-visible absorbtion spectra of these procedures showed that the polysaccharide method produced smaller silver nanoparticles (20 nm), more resistance (2 months) and higher efficiency. Also, TEM imageindicated that the shapes of these particles are spherical. Manuscript profile -
Open Access Article
8 - Comparing A Hybridization of Fuzzy Inference System and Particle Swarm Optimization Algorithm with Deep Learning to Predict Stock Prices
Majid Abdolrazzagh-Nezhad mahdi kheradPredicting stock prices by data analysts have created a great business opportunity for a wide range of investors in the stock markets. But the fact is difficulte, because there are many affective economic factors in the stock markets that they are too dynamic and compl MorePredicting stock prices by data analysts have created a great business opportunity for a wide range of investors in the stock markets. But the fact is difficulte, because there are many affective economic factors in the stock markets that they are too dynamic and complex. In this paper, two models are designed and implemented to identify the complex relationship between 10 economic factors on the stock prices of companies operating in the Tehran stock market. First, a Mamdani Fuzzy Inference System (MFIS) is designed that the fuzzy rules set of its inference engine is found by the Particle Swarm Optimization Algorithm (PSO). Then a Deep Learning model consisting of 26 neurons is designed wiht 5 hidden layers. The designed models are implemented to predict the stock prices of nine companies operating on the Tehran Stock Exchange. The experimental results show that the designed deep learning model can obtain better results than the hybridization of MFIS-PSO, the neural network and SVM, although the interperative ability of the obtained patterns, more consistent behavior with much less variance, as well as higher convergence speed than other models can be mentioned as significant competitive advantages of the MFIS-PSO model Manuscript profile -
Open Access Article
9 - Using a multi-objective optimization algorithm for tasks allocate in the cloud-based systems to reduce energy consumption
sara tabaghchimilan nima jafari novimipourNowadays, new technologies have increased the demand for business in the web environment.Increasing demand will increase the variety and number of services. As a result, the creation of large-scale computing data centers has high operating costs and consumes huge amount MoreNowadays, new technologies have increased the demand for business in the web environment.Increasing demand will increase the variety and number of services. As a result, the creation of large-scale computing data centers has high operating costs and consumes huge amounts of electrical power. On the other hand, inadequate and inadequate cooling systems not only cause excessive heating of resources and shorten the life of the machines. It also produces carbon that plays an important role in the weather. Therefore, they should reduce the total energy consumption of these systems with proper methods. In this research, an efficient energy management approach is provided in virtual cloud data centers, which reduces energy consumption and operational costs, and brings about an increase in the quality of services. It aims to provide a resource allocation strategy for cloud systems with the goal of reducing energy, cost of implementation and examining its use in cloud computing. The results of the simulation show that the proposed method in comaprision to NPA, DVFS, ST and MM methods can reduce the average energy consumption up to 0.626 kWh, also the need to immigration and SLA violation declined up to 186 and 30.91% respectively. Manuscript profile -
Open Access Article
10 - Synthesis of smart nanoparticles polymer for extraction of phenoxy acid herbicides from water samples
Majid Tashi Gholam Abbas Fanaei Kheirabad sogol mirzaei Mehrdad pakzad Oskooi noorbakhsh Mirzaei Heydariyan Dehkordi هادی تابانیDue to their high polarity andsolubility in water these acidic herbicides can be released from harvest fields and therefore pollute surface and ground waters. The World Health Organization (WHO) regulations set 70 ng mL−1 as the maximum contaminant level (MCL) of phenox MoreDue to their high polarity andsolubility in water these acidic herbicides can be released from harvest fields and therefore pollute surface and ground waters. The World Health Organization (WHO) regulations set 70 ng mL−1 as the maximum contaminant level (MCL) of phenoxy acid herbicidesin drinking water [2]. Therefore, the presence of these chemicals inwater sources is highly objectionable for human and animal consumption. Due to the fact that the major sources of drinking water are ground water and river water, monitoring the acidic and polar herbicides in these water sources is quite necessary. Therefore, in this study, we focused on introducing a novel microgel sorbent in which the adsorption and desorption of analytes are controlled only by changing the pH value of the sample. To the best of our knowledge, it is the first report on employing a pH-sensitive magnetic microgel as a new sorbent. In order to increase the adsorption efficiency and rapidly separatethe sorbent from the sample matrix by an external magnetic field, microgel was grafted on magnetic nanoparticles. Finally, the optimized procedure was employed to determine these phenoxy acid herbicides in river water samples. Manuscript profile -
Open Access Article
11 - Revision of Shams-e Tabrizi Sayings from Linguistics and Modern Criticism Perspective
manzar soltani Nafiseh MoradiThere is just one work left from Shams-e Al-Din- Muhammad-e Tabrizi, great mystic of 7th Century Hegira, which is collected and written by his students from his sayings and they called it “Maqalate (the Articles of) Shams-e Tabrizi”. Since his students granted his sayin MoreThere is just one work left from Shams-e Al-Din- Muhammad-e Tabrizi, great mystic of 7th Century Hegira, which is collected and written by his students from his sayings and they called it “Maqalate (the Articles of) Shams-e Tabrizi”. Since his students granted his sayings a specific holiness, they exactly had written whatever he said in most cases and this caused the language of articles to be close to speech language. Reviewing text of articles and indeed reviewing the speech method of Shams, we may come to this conclusion that he had used syntactic and linguistic deconstruction and extra-linguistic facilities to create a unique work that expresses a global and human thought and is not limited within time and space; so that he himself says that its audiences may be born many years later. Shams’ techniques and methods to communicate with his audience and reconstruction of his intuitive mystic experiences are currently under hot discussions by literary critics, linguists and modern hermeneutic scholars. This article reviews the text of Maqalat and compares Shams’ comments, particularly on lexicon and meaning, and analyzed syntactic and linguistic deconstructions of Maqalat’s text and contrasts them with comments of contemporary linguists to explain this issue that Shams was an antecessor thinker and mystic in Mystical Literature who created a work beyond time and space with his literary and unique genius which can be readout in new environment of literary sciences and involves many linguistic theories. Manuscript profile -
Open Access Article
12 - Reviewing and Criticism of Research Articles on Literature in 1380 (2000) Decade
عبدالله راز Ahmad raziPublishing research articles in contemporary period is an appropriate chance to share research findings of different scholars and informing audiences about new scientific achievements. Although their publishing have been quantitatively increasing in recent decade, there MorePublishing research articles in contemporary period is an appropriate chance to share research findings of different scholars and informing audiences about new scientific achievements. Although their publishing have been quantitatively increasing in recent decade, there were no due attention to their assessment and criticism. This article, with a descriptive-analytic method, assesses those kinds of research articles published from 1381/2001 to 1390/2011. The research expresses advantages and disadvantages of these articles and presents a picture of the status of scientific article writing in domain of literary studies. In so doing, 345 articles were selected as examples and most important subjects under focus of authors were identified and were classified in frame of text-based, context-based, author-based, reader-based, and different articles. Moreover, patterns of cooperation between authors, and quality and quantity of used resources in these articles were presented in different charts and tables. As this issue is so important and to assess the accuracy of obtained results from main sample size, another set of 345 articles were exactly reviewed in two groups of “evidence 1” and “evidence 2”. This review shows that although articles have various subjects, apply different kinds of resources, consider some interdisciplinary approaches particularly in second half of this decade relative accuracy in composing coherent articles, specialty of some journals related to literature and considerable increase of university instructors and students cooperation in publishing articles, there are lots of deficiencies in these articles, like methodology, dominance of descriptive approach, repeated contents, lack of critical view, high frequency of education-based articles, and spread of quantitative and formal criteria and so on… Manuscript profile -
Open Access Article
13 - A Survey to the Study of Khayyam during the 14th Century
كاووس حسنلي Saeed HessampourA big variety of woks have been appeared about Omar Khayyam, the Iranian scientist and poet, which study his prominent works and particularly his Ruba’iyat (quartets). Yet, there are lots of basic gaps in the process of this study. In a general view, we can divide the w MoreA big variety of woks have been appeared about Omar Khayyam, the Iranian scientist and poet, which study his prominent works and particularly his Ruba’iyat (quartets). Yet, there are lots of basic gaps in the process of this study. In a general view, we can divide the writings on Khayyam, historically into two periods: writings before the year 1300 (Iranian Year), and writings after the year 1300. There are lots of controversies among the literature on Khayyam before this period. Development of the literature on Khayyam after 1300 was mostly influenced by Fitz Gerald’s translation of Ruba’iyat from Farsi into English because it not only attracted the world’s attention to Khayyam and Iran, but also caused Iranian researchers to do their researches carefully and with more speculation. However, the controversies among the ancient literature, as well as diverse views among the researchers resulted in different approaches to the point in the field of modern studies of Khayyam. The authors of the present article, in the course of a research project which lasted nearly three years, studied all the original Iranian works appeared between 1300 and 1380 about Khayyam, as well as ones translated into Farsi from other languages. What here is presented is a general survey to the study of Khayyam during the current century. The article provides Time and Content tables and figures. Manuscript profile -
Open Access Article
14 - Investigating the Role of Conceptual Metaphors in the Evolution of literary styles (Relying on Body Metaphors in Farrokhi Sistani, Anvari, and Hafiz's poems)
Mohammad Taheri Masoumeh ArchandaniThe conceptual metaphor is the mind’s technique for conceptualizing affairs. The mind tries to conceive and contemplate some intangible affairs for itself with the help of this fundamental construct. Hence, it is expected that by changing it, we will also see a change i MoreThe conceptual metaphor is the mind’s technique for conceptualizing affairs. The mind tries to conceive and contemplate some intangible affairs for itself with the help of this fundamental construct. Hence, it is expected that by changing it, we will also see a change in thought-related macro-systems. Among these macrosystems are literary styles that have many factors involved in changing them. This article tries to answer the question of how the change of conceptual metaphors in time has an effect on the change of literary styles through analytical-descriptive method. To answer it, we trace the conceptual metaphors related to the body, which include the words "hand, eye, heart and head", in a selection of poems by Farrokhi Sistani, Anvari and Hafez. By analyzing the obtained information, we conclude that conceptual metaphors have undergone significant changes over time that are in line with the evolution of literary styles and are variables affecting the evolution of styles. Manuscript profile -
Open Access Article
15 - Multimodal Biometric Recognition Using Particle Swarm Optimization-Based Selected Features
Sara Motamed Ali Broumandnia Azam sadat NourbakhshFeature selection is one of the best optimization problems in human recognition, which reduces the number of features, removes noise and redundant data in images, and results in high rate of recognition. This step affects on the performance of a human recognition system MoreFeature selection is one of the best optimization problems in human recognition, which reduces the number of features, removes noise and redundant data in images, and results in high rate of recognition. This step affects on the performance of a human recognition system. This paper presents a multimodal biometric verification system based on two features of palm and ear which has emerged as one of the most extensively studied research topics that spans multiple disciplines such as pattern recognition, signal processing and computer vision. Also, we present a novel Feature selection algorithm based on Particle Swarm Optimization (PSO). PSO is a computational paradigm based on the idea of collaborative behavior inspired by the social behavior of bird flocking or fish schooling. In this method, we used from two Feature selection techniques: the Discrete Cosine Transforms (DCT) and the Discrete Wavelet Transform (DWT). The identification process can be divided into the following phases: capturing the image; pre-processing; extracting and normalizing the palm and ear images; feature extraction; matching and fusion; and finally, a decision based on PSO and GA classifiers. The system was tested on a database of 60 people (240 palm and 180 ear images). Experimental results show that the PSO-based feature selection algorithm was found to generate excellent recognition results with the minimal set of selected features. Manuscript profile -
Open Access Article
16 - A Learning Automata Approach to Cooperative Particle Swarm Optimizer
Mohammad Hasanzadeh meybodi meybodi mohamad mehdi ebadzadeThis paper presents a modification of Particle Swarm Optimization (PSO) technique based on cooperative behavior of swarms and learning ability of an automaton. The approach is called Cooperative Particle Swarm Optimization based on Learning Automata (CPSOLA). The CPSOLA MoreThis paper presents a modification of Particle Swarm Optimization (PSO) technique based on cooperative behavior of swarms and learning ability of an automaton. The approach is called Cooperative Particle Swarm Optimization based on Learning Automata (CPSOLA). The CPSOLA algorithm utilizes three layers of cooperation which are intra swarm, inter swarm and inter population. There are two active populations in CPSOLA. In the primary population, the particles are placed in all swarms and each swarm consists of multiple dimensions of search space. Also there is a secondary population in CPSOLA which is used the conventional PSO's evolution schema. In the upper layer of cooperation, the embedded Learning Automaton (LA) is responsible for deciding whether to cooperate between these two populations or not. Experiments are organized on five benchmark functions and results show notable performance and robustness of CPSOLA, cooperative behavior of swarms and successful adaptive control of populations. Manuscript profile -
Open Access Article
17 - PSO-Algorithm-Assisted Multiuser Detection for Multiuser and Inter-symbol Interference Suppression in CDMA Communications
Atefeh Haji Jamali Arani paeez azmiApplying particle swarm optimization (PSO) algorithm has become a widespread heuristic technique in many fields of engineering. In this paper, we apply PSO algorithm in additive white Gaussian noise (AWGN) and multipath fading channels. In the proposed method, PSO algor MoreApplying particle swarm optimization (PSO) algorithm has become a widespread heuristic technique in many fields of engineering. In this paper, we apply PSO algorithm in additive white Gaussian noise (AWGN) and multipath fading channels. In the proposed method, PSO algorithm was applied to solve joint multiuser and inter-symbol interference (ISI) suppression problems in the code-division multiple-access (CDMA) systems over multipath Rayleigh fading channel and consequently, to reduce the computational complexity. At the first stage, to initialize the POS algorithm, conventional detector (CD) was employed. Then, time-varying acceleration coefficients (TVAC) were used in the PSO algorithm. The simulation results indicated that the performance of PSO-based multiuser detection (MUD) with TVAC is promising and it is outperforming the CD. Manuscript profile -
Open Access Article
18 - Hybrid Task Scheduling Method for Cloud Computing by Genetic and PSO Algorithms
Amin Kamalinia Ali GhaffariCloud computing makes it possible for users to use different applications through the internet without having to install them. Cloud computing is considered to be a novel technology which is aimed at handling and providing online services. For enhancing efficiency in cl MoreCloud computing makes it possible for users to use different applications through the internet without having to install them. Cloud computing is considered to be a novel technology which is aimed at handling and providing online services. For enhancing efficiency in cloud computing, appropriate task scheduling techniques are needed. Due to the limitations and heterogeneity of resources, the issue of scheduling is highly complicated. Hence, it is believed that an appropriate scheduling method can have a significant impact on reducing makespans and enhancing resource efficiency. Inasmuch as task scheduling in cloud computing is regarded as an NP complete problem; traditional heuristic algorithms used in task scheduling do not have the required efficiency in this context. With regard to the shortcomings of the traditional heuristic algorithms used in job scheduling, recently, the majority of researchers have focused on hybrid meta-heuristic methods for task scheduling. With regard to this cutting edge research domain, we used HEFT (Heterogeneous Earliest Finish Time) algorithm to propose a hybrid meta-heuristic method in this paper where genetic algorithm (GA) and particle swarm optimization (PSO) algorithms were combined with each other. The results of simulation and statistical analysis of proposed scheme indicate that the proposed algorithm, when compared with three other heuristic and a memetic algorithms, has optimized the makespan required for executing tasks. Manuscript profile -
Open Access Article
19 - Lifetime Improvement Using Cluster Head Selection and Base Station Localization in Wireless Sensor Networks
maryam najimi Sajjad NankhoshkiThe limited energy supply of wireless sensor networks poses a great challenge for the deployment of wireless sensor nodes. In this paper, a sensor network of nodes with wireless transceiver capabilities and limited energy is considered. Clustering is one of the most eff MoreThe limited energy supply of wireless sensor networks poses a great challenge for the deployment of wireless sensor nodes. In this paper, a sensor network of nodes with wireless transceiver capabilities and limited energy is considered. Clustering is one of the most efficient techniques to save more energy in these networks. Therefore, the proper selection of the cluster heads plays important role to save the energy of sensor nodes for data transmission in the network. In this paper, we propose an energy efficient data transmission by determining the proper cluster heads in wireless sensor networks. We also obtain the optimal location of the base station according to the cluster heads to prolong the network lifetime. An efficient method is considered based on particle swarm algorithm (PSO) which is a nature inspired swarm intelligence based algorithm, modelled after observing the choreography of a flock of birds, to solve a sensor network optimization problem. In the proposed energy- efficient algorithm, cluster heads distance from the base station and their residual energy of the sensors nodes are important parameters for cluster head selection and base station localization. The simulation results show that our proposed algorithm improves the network lifetime and also more alive sensors are remained in the wireless network compared to the baseline algorithms in different situations. Manuscript profile -
Open Access Article
20 - Social Groups Detection in Crowd by Using Automatic Fuzzy Clustering with PSO
Ali Akbari Hassan Farsi Sajad MohammadzadehDetecting social groups is one of the most important and complex problems which has been concerned recently. This process and relation between members in the groups are necessary for human-like robots shortly. Moving in a group means to be a subsystem in the group. In o MoreDetecting social groups is one of the most important and complex problems which has been concerned recently. This process and relation between members in the groups are necessary for human-like robots shortly. Moving in a group means to be a subsystem in the group. In other words, a group containing two or more persons can be considered to be in the same direction of movement with the same speed of movement. All datasets contain some information about trajectories and labels of the members. The aim is to detect social groups containing two or more persons or detecting the individual motion of a person. For detecting social groups in the proposed method, automatic fuzzy clustering with Particle Swarm Optimization (PSO) is used. The automatic fuzzy clustering with the PSO introduced in the proposed method does not need to know the number of groups. At first, the locations of all people in frequent frames are detected and the average of locations is given to automatic fuzzy clustering with the PSO. The proposed method provides reliable results in valid datasets. The proposed method is compared with a method that provides better results while needs training data for the training step, but the proposed method does not require training at all. This characteristic of the proposed method increases the ability of its implementation for robots. The indexing results show that the proposed method can automatically find social groups without accessing the number of groups and requiring training data at all. Manuscript profile -
Open Access Article
21 - A Two-Stage Multi-Objective Enhancement for Fused Magnetic Resonance Image and Computed Tomography Brain Images
Leena Chandrashekar A Sreedevi AsundiMagnetic Resonance Imaging (MRI) and Computed Tomography (CT) are the imaging techniques for detection of Glioblastoma. However, a single imaging modality is never adequate to validate the presence of the tumor. Moreover, each of the imaging techniques represents a diff MoreMagnetic Resonance Imaging (MRI) and Computed Tomography (CT) are the imaging techniques for detection of Glioblastoma. However, a single imaging modality is never adequate to validate the presence of the tumor. Moreover, each of the imaging techniques represents a different characteristic of the brain. Therefore, experts have to analyze each of the images independently. This requires more expertise by doctors and delays the detection and diagnosis time. Multimodal Image Fusion is a process of generating image of high visual quality, by fusing different images. However, it introduces blocking effect, noise and artifacts in the fused image. Most of the enhancement techniques deal with contrast enhancement, however enhancing the image quality in terms of edges, entropy, peak signal to noise ratio is also significant. Contrast Limited Adaptive Histogram Equalization (CLAHE) is a widely used enhancement technique. The major drawback of the technique is that it only enhances the pixel intensities and also requires selection of operational parameters like clip limit, block size and distribution function. Particle Swarm Optimization (PSO) is an optimization technique used to choose the CLAHE parameters, based on a multi objective fitness function representing entropy and edge information of the image. The proposed technique provides improvement in visual quality of the Laplacian Pyramid fused MRI and CT images. Manuscript profile -
Open Access Article
22 - Evaluation of Pattern Recognition Techniques in Response to Cardiac Resynchronization Therapy (CRT)
Mohammad Nejadeh Peyman Bayat Jalal Kheirkhah Hassan MoladoustCardiac resynchronization therapy (CRT) improves cardiac function in patients with heart failure (HF), and the result of this treatment is decrease in death rate and improving quality of life for patients. This research is aimed at predicting CRT response for the progno MoreCardiac resynchronization therapy (CRT) improves cardiac function in patients with heart failure (HF), and the result of this treatment is decrease in death rate and improving quality of life for patients. This research is aimed at predicting CRT response for the prognosis of patients with heart failure under CRT. According to international instructions, in the case of approval of QRS prolongation and decrease in ejection fraction (EF), the patient is recognized as a candidate of implanting recognition device. However, regarding many intervening and effective factors, decision making can be done based on more variables. Computer-based decision-making systems especially machine learning (ML) are considered as a promising method regarding their significant background in medical prediction. Collective intelligence approaches such as particles swarm optimization (PSO) algorithm are used for determining the priorities of medical decision-making variables. This investigation was done on 209 patients and the data was collected over 12 months. In HESHMAT CRT center, 17.7% of patients did not respond to treatment. Recognizing the dominant parameters through combining machine recognition and physician’s viewpoint, and introducing back-propagation of error neural network algorithm in order to decrease classification error are the most important achievements of this research. In this research, an analytical set of individual, clinical, and laboratory variables, echocardiography, and electrocardiography (ECG) are proposed with patients’ response to CRT. Prediction of the response after CRT becomes possible by the support of a set of tools, algorithms, and variables. Manuscript profile -
Open Access Article
23 - Improvement of Firefly Algorithm using Particle Swarm Optimization and Gravitational Search Algorithm
Mahdi TouraniEvolutionary algorithms are among the most powerful algorithms for optimization, Firefly algorithm (FA) is one of them that inspired by nature. It is an easily implementable, robust, simple and flexible technique. On the other hand, Integration of this algorithm with ot MoreEvolutionary algorithms are among the most powerful algorithms for optimization, Firefly algorithm (FA) is one of them that inspired by nature. It is an easily implementable, robust, simple and flexible technique. On the other hand, Integration of this algorithm with other algorithms, can be improved the performance of FA. Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) are suitable and effective for integration with FA. Some method and operation in GSA and PSO can help to FA for fast and smart searching. In one version of the Gravitational Search Algorithm (GSA), selecting the K-best particles with bigger mass, and examining its effect on other masses has a great help for achieving the faster and more accurate in optimal answer. As well as, in Particle Swarm Optimization (PSO), the candidate answers for solving optimization problem, are guided by local best position and global best position to achieving optimal answer. These operators and their combination with the firefly algorithm (FA) can improve the performance of the search algorithm. This paper intends to provide models for improvement firefly algorithm using GSA and PSO operation. For this purpose, 5 scenarios are defined and then, their models are simulated using MATLAB software. Finally, by reviewing the results, It is shown that the performance of introduced models are better than the standard firefly algorithm. Manuscript profile -
Open Access Article
24 - The history of the concept of the articles of faith in Sunni theological tradition
The discussion of the principles of religion or the articles of faith is one of the most important discussions among Muslim thinkers. This important concept of the principles of religion or the articles of faith has its own history among Muslims. The concept of the five MoreThe discussion of the principles of religion or the articles of faith is one of the most important discussions among Muslim thinkers. This important concept of the principles of religion or the articles of faith has its own history among Muslims. The concept of the five articles of faith in Islam is not extant in Quran or in Hadith but has entered the works of Muslim theologians especially by the works of Mutazilites. In its early stages in the history, the concept of principles of the religion or the articles of faith was used in a general way and referred to the whole theological beliefs but later its usage has narrowed and just referred to some special theological creeds. In this period usually five items were referred to as the five principles of religion. Different theological traditions have their own principles of religion in the way that sometimes seven and even fifteen items were referred to as the principles of religion. Unlike the rationalist Mutazilites, there is no such a concept among Ash'arites or Maturidites. In this article we will survey the history of the changes the concept of the articles of faith experienced in Sunni Kalam tradition Manuscript profile -
Open Access Article
25 - The basis of philosophy of contract realization
jalil ghanavati omid gholamalitabar firozjaieeBasically, the philosophy of contract realization is based on two theories: a view based on formalism and the restraints of the words and specific forms for conclusion of the contract, and the other is based on the freedom of will in concluding the contract. However, af MoreBasically, the philosophy of contract realization is based on two theories: a view based on formalism and the restraints of the words and specific forms for conclusion of the contract, and the other is based on the freedom of will in concluding the contract. However, after the Renaissance, intense oppositions to formality began and the sovereignty of will has grown steadily, and this transformation and attitude has also become more objective in the legal system of Iran after the constitutional revolution, but after a while a lot of criticism, philosophically or legally, appeared regarding it and its severity and intensity has been reduced. In Iran's law, by setting Article 10 of the Civil Code as well as Article 957, the legislator has shown tendency to the principle of sovereignty of will, but this does not mean that we interpret the traditional and jurisprudential texts according to modern interpretations. Manuscript profile -
Open Access Article
26 - A Hybrid Approach based on PSO and Boosting Technique for Data Modeling in Sensor Networks
hadi shakibian Jalaledin NasiriAn efficient data aggregation approach in wireless sensor networks (WSNs) is to abstract the network data into a model. In this regard, regression modeling has been addressed in many studies recently. If the limited characteristics of the sensor nodes are omitted from c MoreAn efficient data aggregation approach in wireless sensor networks (WSNs) is to abstract the network data into a model. In this regard, regression modeling has been addressed in many studies recently. If the limited characteristics of the sensor nodes are omitted from consideration, a common regression technique could be employed after transmitting all the network data from the sensor nodes to the fusion center. However, it is not practical nor efferent. To overcome this issue, several distributed methods have been proposed in WSNs where the regression problem has been formulated as an optimization based data modeling problem. Although they are more energy efficient than the centralized method, the latency and prediction accuracy needs to be improved even further. In this paper, a new approach is proposed based on the particle swarm optimization (PSO) algorithm. Assuming a clustered network, firstly, the PSO algorithm is employed asynchronously to learn the network model of each cluster. In this step, every cluster model is learnt based on the size and data pattern of the cluster. Afterwards, the boosting technique is applied to achieve a better accuracy. The experimental results show that the proposed asynchronous distributed PSO brings up to 48% reduction in energy consumption. Moreover, the boosted model improves the prediction accuracy about 9% on the average. Manuscript profile -
Open Access Article
27 - New Optimization Approach in the Design of Yagi Uda Antenna
A. A. Lotfi-Neyestanak F. Hojjat KashaniIn this paper, several methods for optimization of a 5-elements Yagi antenna are proposed using genetic algorithm, genetic algorithm inspired by simulated annealing, genetic algorithm based on fuzzy decision making, and particle swarm method. High speed run time of Supe MoreIn this paper, several methods for optimization of a 5-elements Yagi antenna are proposed using genetic algorithm, genetic algorithm inspired by simulated annealing, genetic algorithm based on fuzzy decision making, and particle swarm method. High speed run time of SuperNEC software, it has been used for analyzing the presented methods. The use of genetic algorithm or genetic algorithm inspired by simulated annealing for antenna optimization in a specific frequency band, needs long run time. Besides, reduction of the number of population and the amount of repetition, causes decrease in optimization precision. So, an optimization system base on fuzzy decision making is proposed. In addition, the particle swarm method which has a good convergence rate and good performance has been proposed to obtain a better optimization. The comparison between the proposed optimization methods shows that the genetic based on fuzzy decision making and the particle swarm methods have the best performance and functionality and the least run time. Manuscript profile -
Open Access Article
28 - Multi-Objective Particle Swarm Classifier
Seyed-Hamid ZahiriA multi-objective particle swarm optimization (MOPSO) algorithm has been used to design a classifier which is able to optimize some important pattern recognition indices concurrently. These are Reliability, Score of recognition, and the number of hyperplanes. The propos MoreA multi-objective particle swarm optimization (MOPSO) algorithm has been used to design a classifier which is able to optimize some important pattern recognition indices concurrently. These are Reliability, Score of recognition, and the number of hyperplanes. The proposed classifier can efficiently approximate the decision hyperplanes for separating the different classes in the feature space and dose not have any over-fitting and over-learning problems. Other swarm intelligence based classifiers do not have the capability of simultaneous optimizing aforesaid indices and they also may suffer the over-fitting problem. The experimental results show that the proposed multi-objective classifier can estimate the optimum sets of hyperplanes by approximating the Pareto-front and provide the favorite user's setup for selecting aforesaid indices. Manuscript profile -
Open Access Article
29 - A Two-Stage Method for Classifiers Combination
S. H. Nabavi Karizi E. KabirEnsemble learning is an effective machine learning method that improves the classification performance. In this method, the outputs of multiple classifiers are combined so that the better results can be attained. As different classifiers may offer complementary informat MoreEnsemble learning is an effective machine learning method that improves the classification performance. In this method, the outputs of multiple classifiers are combined so that the better results can be attained. As different classifiers may offer complementary information about the classification, combining classifiers, in an efficient way, can achieve better results than any single classifier. Combining multiple classifiers is only effective if the individual classifiers are accurate and diverse. In this paper, we propose a two-stage method for classifiers combination. In the first stage, by mixture of experts strategy we produce different classifiers and in the second stage by using particle swarm optimization (PSO), we find the optimal weights for linear combination of them. Experimental results on different data sets show that proposed method outperforms the independent training and mixture of experts methods. Manuscript profile -
Open Access Article
30 - Optimization of the Nonlinear Behavior of Power Amplifiers in Satellite Digital Image Transmission Using Particle Swarm Method
A. A. Lotfi-Neyestanak Gh. sowlat Mohammad JahanbakhtNonlinear behavior of the power amplifiers in satellite transmitters causes a lot of errors in digital image transmission. So, even by using a moderate linearizer, the bit error rate (BER) will greatly improve. In this paper, the particle swarm optimization has been use MoreNonlinear behavior of the power amplifiers in satellite transmitters causes a lot of errors in digital image transmission. So, even by using a moderate linearizer, the bit error rate (BER) will greatly improve. In this paper, the particle swarm optimization has been used as an effective method with good conversion speed. Effects of an optimized cubic linearizer on digital image transmission are evaluated. The simulations results for the bit error rate as a function of signal to noise ratio (SNR), third order intercept point (TOI), and noise figure (NF) of low noise amplifier (LNA) are compared with each other. Manuscript profile -
Open Access Article
31 - An Intelligent BGSA Based Method for Feature Selection in a Persian Handwritten Digits Recognition System
N. Ghanbari S. M. Razavi S. H. Nabavi KariziIn this paper, an intelligent feature selection method for recognition of Persian handwritten digits is presented. The fitness function associated with the error in the Persian handwritten digits recognition system is minimized, by selecting the appropriate features, us MoreIn this paper, an intelligent feature selection method for recognition of Persian handwritten digits is presented. The fitness function associated with the error in the Persian handwritten digits recognition system is minimized, by selecting the appropriate features, using binary gravitational search algorithm. Implementation results show that the use of intelligent methods is well able to choose the most effective features for this recognition system. The results of the proposed method in comparison with other similar methods based on genetic algorithm and binary particle method of optimizing indicates the effective performance of the proposed method. Manuscript profile -
Open Access Article
32 - Economical Optimization of Capacity and Operational Strategy for Combined Heat and Power Systems
M. HajinazariAn optimization method has been developed to determine the optimal capacities for the CHP and boiler such that thermal and electrical energy demands can be satisfied with high cost efficiency. The proposed method offers an operational strategy in order to determine the MoreAn optimization method has been developed to determine the optimal capacities for the CHP and boiler such that thermal and electrical energy demands can be satisfied with high cost efficiency. The proposed method offers an operational strategy in order to determine the optimum value for boiler and CHP capacities which maximize an objective function based on the net present value (NPV). The reduction in operational strategy expenses arising from the monetary cost of the credit attainable by air pollution reduction is also taken into account in evaluation of the objective function. The optimal value for boiler and CHP capacities and the resulting projection for the optimal value of the objective function are derived using a hybrid optimization method involving the particle swarm optimization (PSO) and the linear programming algorithms. The viability of the proposed method is demonstrated by analyzing the decision to construct a CHP system for a typical hospital. Manuscript profile -
Open Access Article
33 - Risk-based Static and Dynamics Security Assessment and Its Enhancement with Particle Swarm Optimization Generation Realloca
M. Saeedi H. SeifiSecurity assessment is traditionally checked using a deterministic criterion. Based on that, the system may be considered as secured or unsecured. If an unsecured condition is detected, preventive actions are foreseen to make it secure. Recently, risk based security as MoreSecurity assessment is traditionally checked using a deterministic criterion. Based on that, the system may be considered as secured or unsecured. If an unsecured condition is detected, preventive actions are foreseen to make it secure. Recently, risk based security assessment is used in power systems. In this paper, risk-based static and dynamic security assessment is proposed and a new transient stability index is defined. In this paper, the risk index is used as an objective function in the generation reallocation algorithm. In this algorithm, the security is maintained using the generation reallocation. The algorithm is tested on IEEE 24-bus test system and its capabilities are assessed in comparison with a traditional OPF, in which the security is maintained based on a deterministic criterion. Particle Swarm Optimization (PSO) algorithm is used as the optimization tool. Manuscript profile -
Open Access Article
34 - Designing Optimal Fuzzy Classifier Using Particle Swarm Optimization
Seyed-Hamid ZahiriAn important issue in designing a fuzzy classifier is setting its structural and mathematical fuzzy parameters (e.g., number of rules, antecedents, consequents, types and locations of membership functions). In fact, the variations of these parameters establish a wide MoreAn important issue in designing a fuzzy classifier is setting its structural and mathematical fuzzy parameters (e.g., number of rules, antecedents, consequents, types and locations of membership functions). In fact, the variations of these parameters establish a wide range high dimensional search space, which makes heuristic methods some suitable candidates to solve this problem (designing optimal fuzzy parameters). In this paper, a method is described for this purpose. In presented technique, all fuzzy parameters of a fuzzy classifier, are interpreted in structure of particles and PSO algorithm is employed to find the optimal one. Extensive experimental results on well-known benchmarks and practical pattern recognition problem (automatic target recognition) demonstrate the effectiveness of the proposed method. Manuscript profile -
Open Access Article
35 - Visual Target Tracking Using Geometrical Particle Filter and Analytic Color-Based Histogram Model
N. Ghasemi P. Moallem M. F. SabahiColor is an important feature to describe object in visual tracking. Color-based histogram is used to model the object properly and Bhattacharya distance is also used to measure the error between reference and candidate histogram. Particles filter estimate position of t MoreColor is an important feature to describe object in visual tracking. Color-based histogram is used to model the object properly and Bhattacharya distance is also used to measure the error between reference and candidate histogram. Particles filter estimate position of target while two-dimension affine transformation is used as state of the system. Considering geometric properties of affine transformation as affine group cause two-dimensional mapping of the object to be closer to the real three-dimensional model. Approximation of optimal importance function of particles filter is obtained from Taylor expansion of Bhattacharya distance. Experiments show the accuracy and stability of the proposed tracker for fast and complex movement of a color target versus the gray level geometric particle filtering algorithm. Manuscript profile -
Open Access Article
36 - Multi Objective Network Reconfiguration for Distribution System with Micro-Grids Power Exchange using Max-Min Fuzzy Method and Particle Swarm Optimization Algorithm
A. Fattahi Meyabadi H. SohrabianiA group of small generators and energy storages in the low or medium voltage distribution systems beside of consumers emerge to a new power system called micro grid. Micro grids are designed to have secure and economic operation isolated and connected to the network and MoreA group of small generators and energy storages in the low or medium voltage distribution systems beside of consumers emerge to a new power system called micro grid. Micro grids are designed to have secure and economic operation isolated and connected to the network and exchange electrical energy with distribution system. Hence, they may impact on planning and scheduling of distribution systems. In this case, network reconfiguration is a considerable issue after presenting of micro grids to the system. In the previous studies regarding to this issue, micro grid is considered as a distributed generation which should only produce electricity to the network. In this paper, micro grid is modeled as a power exchanger in the distribution network to study the effect of it on the network reconfiguration. For this purpose, reconfiguration is formulated as a multi objective optimization problem using max-min fuzzy method. In this problem, power loss reduction and load balancing among feeders are two independent objectives and voltage profile, lines congestion, radial network structure and load flow are equality and inequality constraints. Particle swarm algorithm is applied to solve the optimization problem and the reconfiguration over two 33 and 70 buses IEEE test network is shown. Results demonstrate that replacing traditional distribution systems by modern active networks and exchanging power with micro grids can lead to increase the reliability of system and more economic operation. Manuscript profile -
Open Access Article
37 - Joint Blind Equalization and Decoding over Frequency Selective Channels in OFDM Systems Using Particle Filtering Joint Blind Equalization and Decoding over Frequency Selective Channels in OFDM Systems Using Particle Filtering
N. Ghasemi M. F. Sabahi A. R. ForouzanIn this paper a sequential algorithm is proposed for joint blind channel equalization and decoding for orthogonal frequency-division multiplexing (OFDM) in frequency selective channels. This algorithm offers a recursive method to sequentially calculate the posterior pro MoreIn this paper a sequential algorithm is proposed for joint blind channel equalization and decoding for orthogonal frequency-division multiplexing (OFDM) in frequency selective channels. This algorithm offers a recursive method to sequentially calculate the posterior probability for maximum a posteriori (MAP) detection. Recursive calculations are done along the indexes in each OFDM symbol using a particle filter. By defining an appropriate importance function, and a proper prior probability distribution function for the channel tap coefficients (and marginalizing it), an efficient method is presented for joint equalization and channel decoding in OFDM based systems. Performance of the proposed detector is evaluated using computer simulations and its bit error rate is compared with the trained turbo equalizer and a conventional particle filter-based method. The results show that the proposed method outperforms the previously presented particle filter-based method without a need for training data. Manuscript profile -
Open Access Article
38 - Particle Filter with Adaptive Observation Model
H. Haeri H. Sadoghi YazdiParticle filter is an effective tool for the object tracking problem. However, obtaining an accurate model for the system state and the observations is an essential requirement. Therefore, one of the areas of interest for the researchers is estimating the observation fu MoreParticle filter is an effective tool for the object tracking problem. However, obtaining an accurate model for the system state and the observations is an essential requirement. Therefore, one of the areas of interest for the researchers is estimating the observation function according to the learning data. The observation function can be considered linear or nonlinear. The existing methods for estimating the observation function are faced some problems such as: 1) dependency to the initial value of parameters in expectation-maximization based methods and 2) requiring a set of predefined models for the multiple models based methods. In this paper, a new unsupervised method based on the kernel adaptive filters is presented to overcome the above mentioned problems. To do so, least mean squares/ recursive least squares adaptive filters are used to estimate the nonlinear observation function. Here, given the known process function and a sequence of observations, the unknown observation function is estimated. Moreover, to accelerate the algorithm and reduce the computational costs, a sparsification method based on approximate linear dependency is used. The proposed method is evaluated in two applications: time series forecasting and tracking objects in video. Results demonstrate the superiority of the proposed method compared with the existing algorithms. Manuscript profile -
Open Access Article
39 - Placement of AVRs and Reconfiguration of Distribution Networks Simultaneously and Robust Considering Load Uncertainty
M. R. Shakarami Y. Mohammadi Pour: In this paper, optimal locating for AVRs and reconfiguration of distribution networks were assessed simultaneously as an optimization problem. A new objective function was introducing which incorporated several electrical indices including real power losses, reactive More: In this paper, optimal locating for AVRs and reconfiguration of distribution networks were assessed simultaneously as an optimization problem. A new objective function was introducing which incorporated several electrical indices including real power losses, reactive power losses, reliability, voltage profile, voltage stability, and load capacity of lines (MVA). Various load levels were incorporated into the objective function to make sure that switch status in reconfiguration and AVR taps and locations would be robust against load variations. This paper also introduced a new method for calculating the load levels with respect to load uncertainty. It also considered all loads based on a voltage-dependent model. Several scenarios are defined to thoroughly assess the proposed approach. Integer particle swarm optimization algorithm (IPSO) was used to solve the mentioned optimization problem. The results obtained by the simulation of 33-bus and 69-bus standard IEEE .radial power distribution networks demonstrated the effectiveness of the proposed approach Manuscript profile -
Open Access Article
40 - Optimal and Simultaneously Compensation of Active, and Reactive Powers in Power System Using of Plug in Electric Vehicle
f. rashidi H. Feshki FarahaniPlug in electric vehicles besides environment pollution reduction can help power system operation. One of the most important capabilities of them is providing activeand reactive power. This paper considers grid constraints, technical concerns and market price and propos MorePlug in electric vehicles besides environment pollution reduction can help power system operation. One of the most important capabilities of them is providing activeand reactive power. This paper considers grid constraints, technical concerns and market price and proposes a framework to allocate the PEV capacity such that operational cost paid by distribution system operator (DSO) to power provider of active and reactive power is minimized. For this purpose, an objective function is defined that includes the payment for each power provider. This objective function is minimized based on particle swarm optimization subject to grid and vehicles constraints. In this framework, the PEVs compete with generator to produce active and reactive power. In order to accelerate the optimization process and prevent the algorithm from being trapped in local optima, new heuristic approaches are included to the original PSO algorithm. To evaluate the effectiveness of the propose method, it is implemented on the low voltage with 134 customer and including the other power providers and the amount of each participants production and payment cost to each component is determined. Manuscript profile -
Open Access Article
41 - Optimum Design of Out-runner PM BLDC Motor with High Torque Density for Flywheel Applications as Energy Storages: Design, FEA and Fabrication
O. Safdarzadeh H. Torkaman Mohammad Mahdavy FakhrOptimum design of electrical motors may be considered as a complex optimization problem due to the wide variety of mechanical, electrical, electromagnetics parameters, although recently it can be accomplished utilizing heuristic optimization algorithms. In this paper op MoreOptimum design of electrical motors may be considered as a complex optimization problem due to the wide variety of mechanical, electrical, electromagnetics parameters, although recently it can be accomplished utilizing heuristic optimization algorithms. In this paper optimum design of an out-runner PM BLDC motor for flywheel energy storage applications is performed. The optimization utilized particle swarm optimization (PSO) algorithm to achieve maximum torque density. Accordingly, the motor design equations are employed in the fitness function of the algorithm. Based on the random initial values and respecting the designs constraints, the optimum design is achieved. Effectiveness of the algorithm results are verified by finite element analysis (FEA) and motor operating parameters are obtained and analyzed. Finally, the prototype of the motor is fabricated and experimental results are demonstrated to show the applicability of the model and analysis. Manuscript profile -
Open Access Article
42 - Optimal Design of Six-Phase Radial Flux Permanent Magnet Synchronous Generator for Small Scale Wind Turbine Applications
M. E. Moazzen S. A. GholamianThis paper presents optimal design of a six-phase permanent magnet synchronous generator (PMSG) for use in direct drive wind turbines. High Dimensions and manufacturing cost and low efficiency are the disadvantages of generators connected to wind turbines without gearbo MoreThis paper presents optimal design of a six-phase permanent magnet synchronous generator (PMSG) for use in direct drive wind turbines. High Dimensions and manufacturing cost and low efficiency are the disadvantages of generators connected to wind turbines without gearbox because of their low nominal speed. Therefore, the main purpose of this paper is to optimize the design of the PMSG based on the reduction of losses and the construction cost of the generator. For this purpose, the relations governing the design of the radial flux PMSG have been introduced and then a design algorithm has been extracted. Subsequently, by defining a multi-objective optimization problem and using the particle swarm optimization (PSO) algorithm, the optimum design variables are determined in a suitable range and the minimum losses and construction cost of the generator are obtained. The optimal design has been verified by using finite element analysis. Manuscript profile -
Open Access Article
43 - Investigating the Absorption Performance of Ink-Jet Printed Microwave Transmission Line at S Band
Mohammad Momeni-Nasab سیدمنصور بیدکی Mohsen Hadizadeh Masoud MovahhediInk-jet printing technology is one of the most promising printing techniques enabling fabrication of conductive patterns in a one-step and direct process. In this study, a microwave transmission line is fabricated on RO4003C substrate using water-based reactive inks and MoreInk-jet printing technology is one of the most promising printing techniques enabling fabrication of conductive patterns in a one-step and direct process. In this study, a microwave transmission line is fabricated on RO4003C substrate using water-based reactive inks and ink-jet printing technique. The fabricated transmission line structure includes an ink-jet printed silver line, a dielectric layer, and a continuous metallic ground plate. The conductivity of the printed line is measured using Four-point probe method. The electromagnetic wave absorption rate of the printed transmission line is simulated according to the measured conductivity, which proves a good agreement with the measured absorption rate at S band (2-4 GHz frequency range). Manuscript profile -
Open Access Article
44 - Energy-Aware Data Gathering in Rechargeable Wireless Sensor Networks Using Particle Swarm Optimization Algorithm
Vahideh Farahani Leili Farzinvash Mina Zolfy Lighvan Rahim Abri LighvanThis paper investigates the problem of data gathering in rechargeable Wireless Sensor Networks (WSNs). The low energy harvesting rate of rechargeable nodes necessitates effective energy management in these networks. The existing schemes did not comprehensively examine t MoreThis paper investigates the problem of data gathering in rechargeable Wireless Sensor Networks (WSNs). The low energy harvesting rate of rechargeable nodes necessitates effective energy management in these networks. The existing schemes did not comprehensively examine the important aspects of energy-aware data gathering including sleep scheduling, and energy-aware clustering and routing. Additionally, most of them proposed greedy algorithms with poor performance. As a result, nodes run out of energy intermittently and temporary disconnections occur throughout the network. In this paper, we propose an energy-efficient data gathering algorithm namely Energy-aware Data Gathering in Rechargeable wireless sensor networks (EDGR). The proposed algorithm divides the original problem into three phases namely sleep scheduling, clustering, and routing, and solves them successively using particle swarm optimization algorithm. As derived from the simulation results, the EDGR algorithm improves the average and standard deviation of the energy stored in the nodes by 17% and 5.6 times, respectively, compared to the previous methods. Also, the packet loss ratio and energy consumption for delivering data to the sink of this scheme is very small and almost zero Manuscript profile -
Open Access Article
45 - Explanation of the Role of Gamification on Job Satisfaction and Employee Motivation (case study: cosmetic industry(
Shahin Rouhani Rad Mehdi Sabokrou Maasoumeh MohammadiThe purpose of this study is the explanation of the role of gamification on job satisfaction and employee motivation in the cosmetic industry. This research is a positivist nature with a quantitative approach. Also, this research is descriptive and in the type of field MoreThe purpose of this study is the explanation of the role of gamification on job satisfaction and employee motivation in the cosmetic industry. This research is a positivist nature with a quantitative approach. Also, this research is descriptive and in the type of field studies, and in terms of research approach, is quantitative research. The target population of this study is all staff of marketing and sales units in the member of Iran cosmetic industries association whose scope of activity is in Tehran province. In this study for sampling, cluster sampling method has been used. Also, we used Krejcie and Morgan tables to determine the sample size, and 350 members of the target population have been investigated. In this research, two methods of library and field methods (a standard questionnaire consisting of 13 items) have been used for data collection. In order to assure the reliability of the measurement instruments, Cronbach's alpha was used. And for validation, content validity (content validity ratio and content validity index) was used. Also, in order to investigate the relationship between variables and data analysis, paired-samples T-test and SPSS software have been used. The results showed that gamification has an effect on job satisfaction and employee motivation Manuscript profile -
Open Access Article
46 - Multi-Label Feature Selection Using a Hybrid Approach Based on the Particle Swarm Optimization Algorithm
َAzar Rafiei Parham Moradi Abdolbaghi GhaderzadehMulti-label classification is one of the important issues in machine learning. The efficiency of multi-label classification algorithms decreases drastically with increasing problem dimensions. Feature selection is one of the main solutions for dimension reduction in mul MoreMulti-label classification is one of the important issues in machine learning. The efficiency of multi-label classification algorithms decreases drastically with increasing problem dimensions. Feature selection is one of the main solutions for dimension reduction in multi-label problems. Multi-label feature selection is one of the NP solutions, and so far, a number of solutions based on collective intelligence and evolutionary algorithms have been proposed for it. Increasing the dimensions of the problem leads to an increase in the search space and consequently to a decrease in efficiency and also a decrease in the speed of convergence of these algorithms. In this paper, a hybrid collective intelligence solution based on a binary particle swarm optimization algorithm and local search strategy for multi-label feature selection is presented. To increase the speed of convergence, in the local search strategy, the features are divided into two categories based on the degree of extension and the degree of connection with the output of the problem. The first category consists of features that are very similar to the problem class and less similar to other features, and the second category is similar features and less related. Therefore, a local operator is added to the particle swarm optimization algorithm, which leads to the reduction of irrelevant features and extensions of each solution. Applying this operator leads to an increase in the convergence speed of the proposed algorithm compared to other algorithms presented in this field. The performance of the proposed method has been compared with the most well-known feature selection methods on different datasets. The results of the experiments showed that the proposed method has a good performance in terms of accuracy. Manuscript profile -
Open Access Article
47 - Nanoparticles for Tendon Healing and Regeneration
sara javanmardi Dara AziziTendon tissue has limited regeneration potential and usually the consequent formation of scar tissue causes inferior mechanical properties. Nanoparticles could be used in different way to improve tendon healing and regeneration, ranging from scaffolds manufacturing (inc MoreTendon tissue has limited regeneration potential and usually the consequent formation of scar tissue causes inferior mechanical properties. Nanoparticles could be used in different way to improve tendon healing and regeneration, ranging from scaffolds manufacturing (increasing the strength and endurance or anti-adhesions, anti-microbial, and ante inflammatory properties) to gene therapy. This paper aims to summarize the most relevant studies showing the potential application of nanoparticles for tendon tissue regeneration. Manuscript profile -
Open Access Article
48 - Permeability estimation using petrophysical logs and artificial intelligence methods: A case study in the Asmari reservoir of Ahvaz oil field
Abouzar Mohsenipour Bahman Soleimani iman Zahmatkesh Iman VeisiPermeability is one of the most important petrophysical parameters that play a key role in the discussion of production and development of hydrocarbon fields. In this study, first, the magnetic resonance log in Asmari reservoir was evaluated and permeability was calcula MorePermeability is one of the most important petrophysical parameters that play a key role in the discussion of production and development of hydrocarbon fields. In this study, first, the magnetic resonance log in Asmari reservoir was evaluated and permeability was calculated using two conventional methods, free fluid model (Coates) and Schlumberger model or mean T2 (SDR). Then, by constructing a simple model of artificial neural network and also combining it with Imperialist competition optimization (ANN-ICA) and particle swarm (ANN-PSO) algorithms, the permeability was estimated. Finally, the results were compared by comparing the estimated COATES permeability and SDR permeability with the actual value, and the estimation accuracy was compared in terms of total squared error and correlation coefficient. The results of this study showed an increase in the accuracy of permeability estimation using a combination of optimization algorithms with artificial neural network. The results of this method can be used as a powerful method to obtain other petrophysical parameters. Manuscript profile -
Open Access Article
49 - Distributed Target Tracking by Solving Average Consensus Problem on Sensor Network Measurements
Iman Maghsudlu Meysam r. Danaee Hamid ArezumandIn this paper, a new algorithm is presented to drastically reduce communication overhead in distributed (decentralized) single target tracking in a wireless sensor network. This algorithm is based on a new approach to solving the average consensus problem and the use of MoreIn this paper, a new algorithm is presented to drastically reduce communication overhead in distributed (decentralized) single target tracking in a wireless sensor network. This algorithm is based on a new approach to solving the average consensus problem and the use of distributed particle filters. For the algorithm of this paper, unlike the common algorithms that solve an average consensus problem just to approximate the global likelihood function to calculate the particle importance weights in distributed tracking, a new model for observation is presented based on the Gaussian approximation, which only solves the problem Consensus is applied to the mean on the received observations of the nodes in the network (and not to approximate the global likelihood function). These innovations significantly reduce the exchange of information between network nodes and as a result uses much less energy resources. In different scenarios, the efficiency of the proposed algorithm has been compared with the centralized algorithm and the distributed algorithm based on the graph, and the simulation results show that the communication overhead of the network is greatly reduced in exchange for an acceptable drop in tracking accuracy by using our proposed algorithm. Manuscript profile -
Open Access Article
50 - The relationship of Quran with Traditions
علی نصیریObjective(s): There are four ideologies regarding the validity and Manbaee’at (being the primary source) of Quran and the traditions: 1) Quran-orienticism discusses that the only source for perceiving religion is the Holy Quran. 2) Tradition-orienticism argues that re MoreObjective(s): There are four ideologies regarding the validity and Manbaee’at (being the primary source) of Quran and the traditions: 1) Quran-orienticism discusses that the only source for perceiving religion is the Holy Quran. 2) Tradition-orienticism argues that resorting to the Infallibles’(AS) Sunnah is the only source for learning about religion. 3) Quran-orienticism and Tradition-orienticism focuses on the issue that Tradition is the same as Quran in validity and Manbaee’at. 4) Double-orienticism says that Tradition is infereior to Quran with respect to validity and Manbaee’at. Method(s): the present research is based on a descriptive-exploratory method. Thus , for deduction of the Quranic data, the writer has analyzed the content of the Quran. Conclusion : The followers of Quraniyoon movement are in favor of the first ideology while the Akhbaris supports the second one. Allameh Tabatabaee and Shatebi are among the followers of the third ideology. The writer of this article has attemped to address the fourth one. Based on Double-orienticism ideology tradition wit respect to validity and Mabaee’t possses independence. Manuscript profile -
Open Access Article
51 - Identification of Transfer Function Parameters of Brushless DC Motor Using Particle Swarm Algorithm
Ahmad Shirzadi Arash Dehestani Kolagar Mohammad Reza Alizadeh PahlavaniSo far, comprehensive and extensive studies have been conducted on the brushless DC motor (BLDC), and a part of these studies focuses on the estimation of the parameters of the transfer function of this motor. Estimation of BLDC motor transfer function parameters is ess MoreSo far, comprehensive and extensive studies have been conducted on the brushless DC motor (BLDC), and a part of these studies focuses on the estimation of the parameters of the transfer function of this motor. Estimation of BLDC motor transfer function parameters is essential to study motor performance and predict its behavior. Therefore, an efficient, accurate and reliable parameter estimation method is needed. In this article, the problem of estimating the parameters of the transfer function of the inverter-fed BLDC motor set has been solved using particle swarm algorithms (PSO). The results of using this algorithm have been compared with the results of other optimization algorithms. The comparison of these results has shown that the PSO algorithm is an efficient, accurate and reliable method for solving the transfer function parameter estimation problem. Manuscript profile -
Open Access Article
52 - Breaking the foundation in Shams Tabrizi articles
mahmoud Khoramabadi AliَََAkbar AfrasiabPour Ali FatolahiThis article deals with the analysis of the elements that break the foundation from the point of view of Derrida and the analysis of these elements in the articles of Shams and tries to reconstruct the pluralism of meaning in damaging the metaphysical ideas presented in MoreThis article deals with the analysis of the elements that break the foundation from the point of view of Derrida and the analysis of these elements in the articles of Shams and tries to reconstruct the pluralism of meaning in damaging the metaphysical ideas presented in Western philosophy and reach new meanings from the text. Shams Tabrizi's articles have the capacity to achieve countless signs and symbols for multiple meanings with consecutive semantic suspensions. The authors of this article, with descriptive-analytical method based on Derrida's foundation-breaking approach, examine some of these concepts such as the negation of the definition of the unit of truth, the death of the author, the semiotics of post-structuralism, the dominant ideology of the text through the negation of contrasts, values, etc. have done. In Shams's articles, in the field of negation of the definition of the single truth, the truth is not considered an absolute and single thing, but it is placed in the field of interpretive debates and everyone has their own interpretation of it. Contrary to the views of Platonic logos, Shams introduces wisdom and rationalism as completely incomplete in the path of truth and sees it as a veil for the seeker. He does not contrast writing and speech or presence and absence, but beyond these two, he generally considers speech and presence as a veil. Manuscript profile -
Open Access Article
53 - Improving resource allocation in mobile edge computing using gray wolf and particle swarm optimization algorithms
seyed ebrahim dashti saeid shabooeiMobile edge computing improves the experience of end users to achieve appropriate services and service quality. In this paper, the problem of improving resource allocation when offloading tasks based on mobile devices to edge servers in computing systems was investigate MoreMobile edge computing improves the experience of end users to achieve appropriate services and service quality. In this paper, the problem of improving resource allocation when offloading tasks based on mobile devices to edge servers in computing systems was investigated. Some tasks are processed locally and some are offloaded to edge servers. The main issue is that the offloaded tasks for virtual machines in computing networks are properly scheduled to minimize computing time, service cost, computing network waste, and the maximum connection of a task with the network. In this paper, it was introduced using the hybrid algorithm of particle swarm and gray wolf to manage resource allocation and task scheduling to achieve an optimal result in edge computing networks. The comparison results show the improvement of waiting time and cost in the proposed approach. The results show that, on average, the proposed model has performed better by reducing the work time by 10% and increasing the use of resources by 16%. Manuscript profile -
Open Access Article
54 - The synergy effect of nanoparticles of magnesium oxide and antibiotics on Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa
Elham Siasi Mehrabian Sedigheh َAli RafieiAim and Background: Prevalence of multidrug resistant bacteria,to be necessary simultaneous use of metal nanoparticles and antibiotics for synergistic antimicrobial effects. In this study was studied the synergy antimicrobial effect of magnesium oxide nanoparticles spec MoreAim and Background: Prevalence of multidrug resistant bacteria,to be necessary simultaneous use of metal nanoparticles and antibiotics for synergistic antimicrobial effects. In this study was studied the synergy antimicrobial effect of magnesium oxide nanoparticles specific concentrations with antibiotics on the standard strains of Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa. Materials and Methods: After preparation of nano particles and bacteria was used antibiogram by disk diffusion. The antimicrobial properties of nanoparticles were studied by using MIC (Minimum Inhibition concentration) and MBC (Minimum Bactericidal concentration), blank discs and liquid medium. Synergistic effects for bacteria were detected by combining of specific concentration of nanoparticles with antibiotic disks and solution of antibiotics (well-method). Results: The results of the MIC and MBC and liquid medium were confirmed antimicrobial properties of these nanoparticles. E. coli other than the bacteria was more sensitive to lower concentrations of the nanoparticles. Synergistic effect was showed between different concentrations of nanoparticles with methicillin disk in E. coli but, synergistic effect can be observed for three bacteria in the well-method. Conclusion: The results showed synergy effect was observed in all of the bacteria at low concentrations with antibiotics, so this property can be used to reduce the dosage and number of consuming antibiotics. Manuscript profile -
Open Access Article
55 - Investigating the Particle Size of Chitosan-Based Drug Carriers for the Release of 5-Fluorouracil Antitumor Drug
Mohammad Hossein Karami Majid Abdouss Mandana KaramiChitosan has been widely used as a natural biopolymer. The modification of chitosan for various applications can be easily achieved due to the abundant active groups (NH2 and OH) in the main chain. Controlled drug release makes the drug release rate predictable and repe MoreChitosan has been widely used as a natural biopolymer. The modification of chitosan for various applications can be easily achieved due to the abundant active groups (NH2 and OH) in the main chain. Controlled drug release makes the drug release rate predictable and repeatable for prolonged release drugs. Drug delivery systems prepared from nanoparticles show several advantages, including improved efficiency and reduced toxicity. Using drug delivery systems based on nanoparticles loaded with anti-cancer agents is an effective method for targeting cancer cells. These systems, with the ability to penetrate better inside the cells, combine the drug in a targeted way in the cells. Also, due to the enhanced permeability and retention (EPR), the possibility of better accumulation of drugs in the tumor site is provided. In most researches, the suitable particle size for the targeted release of drug nanocarriers has been reported to be less than 300 or 200 nm. This amount is suitable for the application of drug release for diffusion among tissues and causes the effect of increasing permeability. In this study, for the first time, it examines and analyzes the particle size and zeta potential (surface charge) of chitosan-based nanocarriers through dynamic light scattering and electron microscope tests in improving the release of the antitumor drug, 5-fluorouracil. Manuscript profile -
Open Access Article
56 - A review of polymer bonded explosive rheology
Mahmoud HeydariPolymer-bonded explosives are widely used in defense and commercial industries. In this type of explosive, very high amounts of explosive crystals (about 90% by weight) are surrounded by a polymeric binder (about 10%), which leads to a decrease in sensitivity and a sign MorePolymer-bonded explosives are widely used in defense and commercial industries. In this type of explosive, very high amounts of explosive crystals (about 90% by weight) are surrounded by a polymeric binder (about 10%), which leads to a decrease in sensitivity and a significant increase in safety during application and storage. These mixtures are molded in different ways, such as pressing, casting, extrusion, and injection. Studying the rheology of these mixtures with a high percentage of solid loading leads to finding the appropriate quality control method at different production stages. The first step was to review studies on alternatives to simulating explosive rheological behavior, such as dechlorane, calcium carbonate, sugar, etc. The general behavior of simulated mixtures, such as yield stress, shear rate dependence, time dependence, etc., is compared with original explosive. The results showed that despite the similarity in some rheological behaviors, it is impossible to predict and study all the rheological behaviors of polymer-bonded explosives using simulating materials. This paper discusses factors affecting the rheology of polymer-bonded explosives, such as particle size distribution, modification of explosive crystal surfaces, and plasticizer. A review of scientific sources showed that using a wide distribution of explosive crystal particles compared to a narrow distribution led to a significant reduction in viscosity and dependence on shear rate and time. The absence of strong interactions between crystal particles and polymer binder leads to no observation of quasi-solid behavior even in 85% by weight of explosive crystals such as octogen in hydroxyl-terminated polybutadiene Manuscript profile -
Open Access Article
57 - Investigating the Particle Size of Chitosan-Based Drug Carriers for the Release of 5-Fluorouracil Antitumor Drug
Mohammad Hossein Karami Majid Abdouss Mandana KaramiChitosan has been widely used as a natural biopolymer. The modification of chitosan for various applications can be easily achieved due to the abundant active groups (NH2 and OH) in the main chain. Controlled drug release makes the drug release rate predictable and repe MoreChitosan has been widely used as a natural biopolymer. The modification of chitosan for various applications can be easily achieved due to the abundant active groups (NH2 and OH) in the main chain. Controlled drug release makes the drug release rate predictable and repeatable for prolonged release drugs. Drug delivery systems prepared from nanoparticles show several advantages, including improved efficiency and reduced toxicity. Using drug delivery systems based on nanoparticles loaded with anti-cancer agents is an effective method for targeting cancer cells. These systems, with the ability to penetrate better inside the cells, combine the drug in a targeted way in the cells. Also, due to the enhanced permeability and retention (EPR), the possibility of better accumulation of drugs in the tumor site is provided. In most researches, the suitable particle size for the targeted release of drug nanocarriers has been reported to be less than 300 or 200 nm. This amount is suitable for the application of drug release for diffusion among tissues and causes the effect of increasing permeability. In this study, for the first time, it examines and analyzes the particle size and zeta potential (surface charge) of chitosan-based nanocarriers through dynamic light scattering and electron microscope tests in improving the release of the antitumor drug, 5-fluorouracil. Manuscript profile -
Open Access Article
58 - Improving Resource Allocation in Mobile Edge Computing Using Particle Swarm and Gray Wolf Optimization Algorithms
seyed ebrahim dashti saeid shabooeiMobile edge computing improves the experience of end users to achieve appropriate services and service quality. In this paper, the problem of improving resource allocation, when offloading tasks, based on mobile devices to edge servers in computing systems is investigat MoreMobile edge computing improves the experience of end users to achieve appropriate services and service quality. In this paper, the problem of improving resource allocation, when offloading tasks, based on mobile devices to edge servers in computing systems is investigated. Some tasks are uploaded and processed locally and some to edge servers. The main issue is that the offloaded tasks for virtual machines in computing networks are properly scheduled to minimize computing time, service cost, computing network waste, and the maximum connection of a task with the network. In this paper, a multi-objective hybrid algorithm of particle swarm and gray wolf was introduced to manage resource allocation and task scheduling to achieve an optimal result in edge computing networks. Local search in the particle swarm algorithm has good results in the problem, but it will cause the loss of global optima, so in this problem, in order to improve the model, the gray wolf algorithm was used as the main basis of the proposed algorithm, in the wolf algorithm Gray, due to the graphical approach to the problem, the set of global searches will reach the optimal solution, so by combining these functions, we tried to improve the operational conditions of the two algorithms for the desired goals of the problem. In order to create a network in this research, the network creation parameters in the basic article were used and the LCG data set was used in the simulation. The simulation environment in this research is the sim cloud environment. The comparison results show the improvement of waiting time and cost in the proposed approach. The results show that, on average, the proposed model has performed better by reducing the work time by 10% and increasing the use of resources by 16%. Manuscript profile
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