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    • Open Access Article

      گروه‌بندی همسان یادگیرندگان در محیط یادگیری الکترونیکی به کمک روش خوشه¬بندی شورایی
         
      Number39 , Year 11 , SpringSummer 2019
      Despite the individual differences of learners such as their abilities, goals, knowledge, learning styles and backgrounds, most of the electronic learning systems has presented an equal learning content for all of the learners. This is happening while producing a specia Full Text
      Despite the individual differences of learners such as their abilities, goals, knowledge, learning styles and backgrounds, most of the electronic learning systems has presented an equal learning content for all of the learners. This is happening while producing a specialized content for the individuals. Increasing appliances of artificial memory in teaching the adaptation learning systems will require recommended teaching methods which are appropriate to the learner’s individual differences. In order to grouping learners based on their learning styles in their own similar groups, we are presenting a new method in this text. This method is mainly about combining the result of clustering methods which is certainly reducing choosing an unreliable method. Meanwhile it is preventing method`s complication which is because of using simpler and more useful clustering algorithms that subsequently will cause a better result and it may happen due to the fact that different methods will overlap each other’s defections. In this article we are using Felder- Silverman learning style which consist of 5 dimensions: processing (active-reflective) , input (visual-verbal) , understanding (sequential-global) , perception (sensing-intuitive) and organization (inductive-deductive). Firstly, proper behavioral indicators to different learning style dimension of Silverman-Feedler will recognize and then based on these behaviors learners will be able to be groups by one of these 5 methods. In the case of evaluating the proposed method, utilizing the c++ programming electronic teaching period information is necessary. Learner members of experiment environment were 98 ones which were extracting the expressed indicators connected to their network behaviors in 4 dimensions of Perception , process , input and understanding of Felder- Silverman model. On the other hand students were asked to fill the questionnaire forms and their learning styles were calculated between 0-11 and then based on the behavioral information they were being grouped. We are using 5 clustering grouping methods : k-means , FCM , KNN , K-Medoids and SVM to produce ensemble clustering in generation step and co-occurrence samples or majority votes were used in Integration step. Evaluating the results will require the followings : Davies-bouldin index , Variance index , and gathering purity index. Due to the fact that the expressed methods are not able to indicate automatically the best cluster, clustering 3,4,5,6,7 clusters were using this method. And with calculating Davies-bouldin index the best cluster in each method were selected. In FCM each data were contributed to the cluster which has the most dependence to that . Numerical results of Davies-bouldin index have shown that ensemble clusters have the exact accumulation clusters among the others. Clustering variance in different size is indicating that ensemble clustering has the most accumulation and the least dispersion and also purity-gathering results has shown that proposed grouping method has the ability to gather learners with the similar style in each cluster and has a better efficiency compared to the others. So with this idea while maintaining simplicity, more accurate results based on the Davies-bouldin index , Variance index , and gathering purity index is obtained. Due to the importance of high accuracy and high speed and low computational complexity in the clustering methods, instead of a more complex approach, combining the weaker and easier clustering methods, better and more accurate results reached. Article Details


    • Open Access Article

      Routing improvement to control congestion in software defined networks by using distributed controllers
         
      Number39 , Year 11 , SpringSummer 2019
      Software defined networks (SDNs) are flexible for use in determining network traffic routing because they separate data plane and control plane. One of the major challenges facing SDNs is choosing the right locations to place and distribute controllers; in such a way th Full Text
      Software defined networks (SDNs) are flexible for use in determining network traffic routing because they separate data plane and control plane. One of the major challenges facing SDNs is choosing the right locations to place and distribute controllers; in such a way that the delay between controllers and switches in wide area networks can be reduced. In this regard, most of the proposed methods have focused on reducing latency. But latency is just one factor in network efficiency and overall cost reduction between controllers and related switches. This article examines more factors to reduce the cost between controllers and switches, such as communication link traffic. In this regard, a cluster-based algorithm is provided for network segmentation. Using this algorithm, it can be ensured that each part of the network can reduce the maximum cost (including delays and traffic on links) between the controller and its related switches. In this paper, using Topology Zoo, extensive simulations have been performed under real network topologies. The results of the simulations show that when the probability of congestion in the network increases, the proposed algorithm has been able to control the congestion in the network by identifying the bottleneck links in the communication paths of each node with other nodes. Therefore, considering the two criteria of delay and the degree of busyness of the links, the process of placing and distributing the controllers in the clustering operation has been done with higher accuracy. By doing so, the maximum end-to-end cost between each controller and its related switches, in the topologies Chinanet of China, Uunet of the United States, DFN of Germany, and Rediris of Spain, is decreased 41.2694%, 29.2853%, 21.3805% and 46.2829% respectively. Article Details


    • Open Access Article

      بررسی تاثیر استفاده از انواع استراتژی¬های بازاریابی در شبکه‌های اجتماعی بر جلب اعتماد مشتریان شورایی
         
      Number39 , Year 11 , SpringSummer 2019
      The aim of this study is to investigate the effect of using variety of marketing strategies in social networks to build customers’ trust. Marketing through social networks has made appropriate opportunities for companies to attract more customers. Building customers' tr Full Text
      The aim of this study is to investigate the effect of using variety of marketing strategies in social networks to build customers’ trust. Marketing through social networks has made appropriate opportunities for companies to attract more customers. Building customers' trust and attracting the customers can be mentioned as marketing challenges on these networks. So, in order to create competitive advantages, companies need to use appropriate strategies of building trust. The population of this study consists of all Iranian users of social networking sites that affected by companies advertisements. Also the sample size by using snowball sampling method is 446. The research method is descriptive survey research and data collection tool is questionnaire. To test hypotheses the partial least squares (PLS) technique and SmartPLS 3 software has been used. The results show that all four variables include: transactional, relationship, database and knowledge-based marketing strategies in social networks have a significant impact to build customers’ trust. Indeed, transactional strategy has negative impact on trust so the relation between this variable and dependent variable is reverse. knowledge-based marketing strategy has the most positive impact on customers’ trust. Article Details

    • Open Access Article

      معیارهای ارزیابی ارزش اثرگذاری کاربران رسانه های اجتماعی- چارچوبی براساس کاوش رسانه های اجتماعی
         
      Number39 , Year 11 , SpringSummer 2019
      Nowadays, users' interactive behaviors on social media have become an important and influential resource on marketing activities in various businesses. Despite the importance of this issue, providing appropriate criteria for evaluating the influential behavior of user Full Text
      Nowadays, users' interactive behaviors on social media have become an important and influential resource on marketing activities in various businesses. Despite the importance of this issue, providing appropriate criteria for evaluating the influential behavior of users in recent studies has received less attention. For this purpose, in the first step, an innovative theory framework including two main dimensions: potential of the influence and the level of the influence is presented. Then, in order to define criteria for measuring each dimension, by providing a comprehensive and combined classification including three domains, user-based analysis, relationship-based analysis and content-based analysis, exploration techniques Social media has been examined to analyze the effective behaviors of users. In the following, according to the literature review, the criteria of "number of active users", “ranked of users based on the structural indexes and activity", “quality and the subjectiveness of content” have been defined to measure each of the aforementioned dimensions. The criteria proposed in this article are effective for creating dashboards to assess the value of users' influence in various businesses. It also a comprehensive roadmap has been provided for businesses about the data they need to collect and the required techniques to determine each of these metrics through a cross-disciplinary and academic classification of social media exploration techniques. Article Details