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Open Access Article
1 - IMPLEMENT THE SMART TRAINING SYSTEMS IN THE MOBIL LEARNING WAY
manzar ezzati abarghaniThis research was carried out to consider the effects of the implementation of the smart training systems in the mobile learning way. The research method was semi-experimental. The statistical society of this study was all first boy students in third grade at smart high MoreThis research was carried out to consider the effects of the implementation of the smart training systems in the mobile learning way. The research method was semi-experimental. The statistical society of this study was all first boy students in third grade at smart high schools in Garmsar. The academic year was the first term of 96-97 academic year. The statistical sample was chosen from the high school third grade first students based on the Morgan table and regarding with the society volume. 102 students were chosen in the cluster random method. At first 2 regions were chosen from Garmsar training regions then 2 first high schools was chosen and finally 102 students were selected from the third grade students of these schools. These 102 students were divided randomly into 2 groups (each group had 51 students). The groups were experimental group and control group. Several lessons from English Book were chosen as the training material and before the training, 2 groups gave the pre-test. The control group as usual were trained based on the smart training systems ( smart board , the computer facilities and the technologies related to the electronic management and control) but the experimental group was trained using the smart training systems ( mobile devices such as Tablet and cell phone). After training, the post-test was performed. The obtained data were analyzed using Spss version 18 software in description statistical level (the average and standard deviation) and deductive statistical level (independent T statistical test). The research results showed that the marks of the English lesson for experimental group ( who had been trained using the smart training systems in the mobile learning way) were higher than the marks of the English lesson for control group ( who had been trained using the smart training systems) ( t: 3/353 , sig: 0/001) So we can say that implementing the smart training systems in the mobile learning way have possible effects on the training. Manuscript profile -
Open Access Article
2 - Mobility-Aware and Fault-Tolerant Computation Offloading for Mobile Cloud Computing
R. Roostaei Z. MovahediNowadays, Internet of Things (IoT) has emerged as an important field in information and communication technologies. Despite the progress of networks and communication technologies, the development of IoT has encountered some challenges mainly with regard to computation MoreNowadays, Internet of Things (IoT) has emerged as an important field in information and communication technologies. Despite the progress of networks and communication technologies, the development of IoT has encountered some challenges mainly with regard to computation power, battery lifetime and memory of mobile devices. In order to overcome these challenges, mobile cloud computing has been raised which uses the cloud storage space and computation power to extend the capabilities of mobile devices. In this regard, some of application’s components are selected to be offloaded to the cloud in order to optimize the execution time and energy consumption of application. Since the mobility has an important effect on the acquired condition of the access network and the quality of the connection, the mobility should be considered while selecting components for offloading. Although a number of mobility-aware offloading approaches has been already proposed, these works suffer from the lack of an appropriate mobility-model, ignorance of the fault-tolerance capability and use of only coarse-grain offloading. In order to address these issues, we propose a mobility-aware offloading scheme which uses the user mobility Markov chain and the fault tolerance capability in order to optimize the offloading decision. Evaluation results show that our proposed method significantly outperforms the existing alternatives, reaching respectively up to 75 and 65 percent enhancement in terms of the execution time and the energy consumption. Manuscript profile -
Open Access Article
3 - Feasibility Study of Education Implementation through Mobile in Tehran Municipality
Seyed Mohsen Tabatabaei MozdabadiModern methods of education such as distance education are considered nowadays due to numerous and varied educational needs of organizations on the one hand and the high costs and spending lots of time for education on the other hand . In the meantime it has been accel MoreModern methods of education such as distance education are considered nowadays due to numerous and varied educational needs of organizations on the one hand and the high costs and spending lots of time for education on the other hand . In the meantime it has been accelerated by rapid progresses in technology. This research attempts to study the implementation feasibility of education through mobile as one of subsets of distance education in Tehran municipality. Statistical population of the research was consisted of financial and administrative staff in Tehran municipality. 330 persons were selected among the statistical population as the sample size randomly. The tool for data collection was questionnaire which its validity and reliability has confirmed by standard methods. The single-sample T-test and Friedman test were used for analyzing the data. The results show that Tehran municipality has essential preparation for education implementation through mobile respectively from learner, social and instrumental aspects. Manuscript profile -
Open Access Article
4 - 1. Nori Y.]Intelligent Learning Units will bring mobile learning and technology together. Congratulations from the top e-creator of the electronic content of Guilan province. 2012. available at: http://shabestan.ir/detail/News/227973. 2. Liu X , Toki E I , Pange J. The use of ICT in preschool education in greece and China: A Comparative study. Procedia - Social and Behavioral Sciences,.112,.7,.1167- 76 available at http://www.sciencedirect.com. 2014. 3. Chaharband E. Intelligence of schools on the first subfamily . availableat: http://ijvlms.ir/online/browse.php?a_code=A-10-6-69&sid=1&slc_lang=fa 2017. 4. Sharifi A, Davoudi AH, Islamiyah F. The relationship between the use of information and communication technologies and the performance of teachers in the teaching and learning process , Information and Communication Technology in Educational second year. 4(8). . 2012. 5. HakimZadeh R, Abolghasemi N M, Nejati F. Comparison of the feeling of belonging to the school, the motivation for academic achievement and academic achievement among the students of intelligent schools (ICT) and ordinary schools of the year Third high school in Isfahan. Education Journal. 2013. 6. Noahi S, Hosseini S M, Rokhsarizadeh H, Sabouri A, Alishiri, Gh. ] Evaluation of Achievement Motivation and its Relationship with Academic Achievement in Medical[. Nursing and Health Care Students in a Medical University, Military Medicine14 (3). 200-204. . 2012. 7. Rajabi M. Comparison of the motivation of progress, self-regulation and academic achievement of third-year students of mathematics in ordinary and intelligent schools of Hamadan in the academic year 1392-1391. Master's thesis for educational technology.Arak University. Faculty of Literature and Humanities. 2013. 8. Beheshti Z. The Role of Information and Communication Technologies in Mobile Learning.4 thNational Electrical Engineering Conference on. Islamic Azad University. Najaf Abad branch. Iran, March 15, 16. 2007. 9. Barzegar R, Dehghanzadeh H, Moghadamzadeh A. From E-learning to Mobile Learning Theoretical Foundations. MediaSummer. Volume 3. Number 2. . 2012. 10. El-Hussein N. O , Cronje J. C. Defining mobile learning in the higher educatoin landscape.Educational Technology&Society , 12-21. 2010. 11. Trinder J. Mobile learning evaluation: the development of tools and techniques for the evaluation of learning exploiting mobile devices through the analysis of automatically collected usage logs-an iterative approach .PhD Thesis . Glasgow, Scotland: University of glasgow. 2012. 12. Hashemi M, Ghasemi B. Using Mobile Phones in Language Learning/Teaching. Procedia Social and Behavioral Sciences 15 Internet. p. 2947–51. Available from: http://www.sciencedirect.com. 2011. 13. Lai C. H , Yang J C, Chen F C, Ho Chant T W. Affordances of Mobile Technologies for Experiential Learning: The Interplay of Technology and Pedagogical Practices. Computer Assisted Learning, Vol. 23, PP. 326-37. 2007 14. Zarnagar M. The role of mobile on learning. Available at http://vestasoftware.com/fa/blog/item/11-mlearning.2018. 15. Kashki H, Baghani M. Comparison of the role of teachers in synchronous and non-synchronous environment in e-learning. 2011. Fourth National Conference on Electronic Learning in Medical Sciences. 15-20. 2011. 16. Attewell J. From research and development to mobile learning: Tools for education and training providers and their learner . Retrieved from http://www.mlearn.org.za/cd/papers/Attewell.pdf. 2005. 17. Wang Y S, Wu M C ,Wang H Y. Investigating the determinants and age and gender differences in the acceptance of mobile learning .British Journal of Educational Technology , 92-118. 2009. 18. Jacob S M , Issac B. Mobile learning culture and effects in higher education. Ieee Multidisciplinary Engineering Education Magazine, 2 (2). 2007. 19. Rau P P, Gao Q, Wu L M. Using mobile communication technology in high school education: Motivation, pressure, and learning performance. Computers & Education, 50(1), 1-22. 2008. 20. McConatha D, Matt P, Michael J L. Mobile learning in the classroom: An empirical assessment of a new tool for students and teachers. The Turkish Online Journal of Educational Technology, TOJET, 7 (3), 2. 2008. 21. Dewitte C M. Integrating cell phones into the secondary Montessori classroom Doctoral dissertation, Walden University. Retrieved from http:// udini.proquest.com/view/integrating-cell-phones-intothe- goid:305229558/. 2010. 22. Nyamba S Y, Mlozi M R S. Factors influencing the use of mobile phones in communicating agricultural information: a case of kilolo district, iringa, Tanzania. International Journal of Information and Communication Technology Research, 2(7), 558-63. 2012. 23. Bullock A Does. technology help doctors to access, use and share knowledge? Medical education. 48(1): 28-33.2014. 24. Naderi F, Porshafei H. Mobile Learning: Opportunities and Challenges. Third International Conference on Psychology; Educational Sciences and Lifestyle. Torbat Heydarieh University. https://www.civilica.com/Paper-ICPE03-ICPE03_252.html.2016. 25. Moradi I, Dideban H. The Position of Mobile Learning in Medical Sciences Universities: Opinions, Consequences and Challenges, Teb va Tazkiyeh. Summer. Volume 27. Issue 2. Pages 145-313. 2018. 26. Jahaniyan R, Etebar sh. Evaluation of the Situation of Virtual Education in E-Learning Centers of Universities of Tehran from Students' Perspectives. Information and Communication Technology in Education. 2 (4) 53-65. 2012. 27. Shohel M, Mahruf C, Power T. Introducing mobile technology for enhancing teaching and learning to the English language classroom in Bangladesh. Department of Education, The Open University.2010. 28. ShahMohammadi A M, Kohi F A. Mobile Application and Text Messaging in Science Education. 8th Seminar on Chemistry of Iran. 6th and 7th of September. Semnan University. 2014.
mahmod ekrami manzar ezzati abarghaniAim: The study is aimed to investigate the ways that implementing intelligent educational systems can inform mobile learning. Method: The research method was quasi-experimental. The statistical population is composed of male students of the third-grade secondary school MoreAim: The study is aimed to investigate the ways that implementing intelligent educational systems can inform mobile learning. Method: The research method was quasi-experimental. The statistical population is composed of male students of the third-grade secondary school of Smart in the city of Grammar of the academic year 97-96. According to Morgan schedule, in this study, 102 students of third grade high school from intelligent schools were selected using multistage cluster sampling and were randomly assigned into experimental and control groups. Several lessons from the English language book were selected as the content of the training, and before the training, they were done on both groups of pre-tests. The control group was trained on an intelligent learning system as usual. But the learning group was experimenting with intelligent learning systems through mobile devices (tablets and mobiles). After training, the post-test was performed on both groups. Analyzee: Data were analyzed using SPSSv.18 software in two levels of descriptive and inferential statistics (independent t-test). Results: The results of the study showed that the English language test grades of the experimental group, which were trained using intelligent educational systems in the field of mobile learning, were more than the English language test grades that were taught using intelligent educational systems. So, we can say that the implementation of intelligent educational systems in the context of mobile learning has a positive effect on education. Manuscript profile -
Open Access Article
5 - Improve security in cloud computing infrastructure using block chain protocol
Mohsen Gerami Vahid Yazdanian Siavash NaebaslSecurity in cloud computing is very important, cloud computing security is a set of computer security and network security in general is information security and when a processing task by using the virtual machine scheduling algorithm in the cloud for processing Unloadi MoreSecurity in cloud computing is very important, cloud computing security is a set of computer security and network security in general is information security and when a processing task by using the virtual machine scheduling algorithm in the cloud for processing Unloading will be This virtual machine will not be able to distinguish the normal mobile user from attackers, thus violating the privacy and security of the transmitted data, so after determining the unloading strategy, the China block can be used in information security. And the information of each server is encapsulated and unloaded in the form of a block. In this research, a proposed solution is presented, which is the combination of China blockchain and cloud computing to increase security and efficiency. The proposed solution is implemented and evaluated in order to evaluate its efficiency increase compared to other existing solutions. Manuscript profile -
Open Access Article
6 - A Fast and Lightweight Network for Road Lines Detection Using Mobile-Net Architecture and Different Loss Functions
Pejman Goudarzi milad Heydari Mehdi HosseinpourBy using the line detection system, the relative position of the self-driving cars compared to other cars, the possibility of leaving the lane or an accident can be checked. In this paper, a fast and lightweight line detection approach for images taken from a camera ins MoreBy using the line detection system, the relative position of the self-driving cars compared to other cars, the possibility of leaving the lane or an accident can be checked. In this paper, a fast and lightweight line detection approach for images taken from a camera installed in the windshield of cars is presented. Most of the existing methods consider the problem of line detection in the form of classification at the pixel level. These methods despite having high accuracy, suffer from two weaknesses of having the high computational cost and not paying attention to the general lines content information of the image (as a result, they cannot detect if there is an obstacle). The proposed method checks the presence of lines in each row by using the row-based selection method. Also, the use of Mobile-net architecture has led to good results with fewer learning parameters. The use of three different functions as cost functions, with different objectives, has resulted in obtaining excellent results and considering general content information along with local information. Experiments conducted on the TuSimple video image collection show the suitable performance of the proposed approach both in terms of efficiency and especially in terms of speed. Manuscript profile -
Open Access Article
7 - 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
8 - Investigating the Sociological Causes of the Tendency to Use Mobile Social Networks
Saeed Mohammadi Sadegh hossein ebrahimSocial networks have a significant impact on the collective and individual lives of people, and the amount and scope of their use increases every day. Social factors are among the most decisive factors in the field of using these types of networks. Therefore, in this re MoreSocial networks have a significant impact on the collective and individual lives of people, and the amount and scope of their use increases every day. Social factors are among the most decisive factors in the field of using these types of networks. Therefore, in this research, an attempt has been made to study the effect of these types of factors including family, friends, relatives, ethnicity, media and social base on the use of social networks and its effect on the interpersonal and family relationships of Zahedan youth. The method of this research is the survey and the method of gathering information using a structured interview-based questionnaire tool, and the sample size is 300 people. In order to extract the data of this research from spss software and to analyze the data from the statistical tests of analysis of variance, the correlation coefficient was used for the intensity of the link between the variables along with the significance level of the test (sig). This research aims to answer the questions of how much the youth of Zahedan use mobile social networks? And what are the social factors affecting the use of these mobile social networks by the youth of Zahedan. The results of this research showed that: 49% of respondents use mobile social networks. Social factors such as: interpersonal relationships, family and family relationships, etc. can predict a total of 88.2% of the variance of the dependent variable, i.e. the use of mobile social networks Manuscript profile -
Open Access Article
9 - 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