List of Articles

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  1 - SDC-causing Error Detection and Mitigation Based on Failure rate Prediction without Fault Injection
  Moona Yakhchi Mahdi Fazeli Seyed Amir Asghari Toochai
  20.1001.1.27832570.1401.3.4.1.5
  Introduction: Reducing the size of processing components and increasing the probability of failure even in ordinary components maintaining reliability has become a serious challenge of today’s computer systems. The soft errors can lead to silent data corruption wh More

  Introduction: Reducing the size of processing components and increasing the probability of failure even in ordinary components maintaining reliability has become a serious challenge of today’s computer systems. The soft errors can lead to silent data corruption which seriously compromises the reliability of a system. The Silent data corruption is a fault that affects running software and leads to incorrect output. Detecting silent data corruption needed a profile of the instructions causing the silent data corruption to decide which instructions to be protected. Current approaches by machine learning algorithms predict the occurrence rate of silent data corruption for each instruction. While most of the existing algorithms suffer from inaccuracy. Most current detection techniques require sufficient data from fault injection for training, which is difficult to achieve due to high resource consumption, such as execution time and code size costs. However, as technology is downscaling toward Nano-scale sizes, multiple-bit soft errors are emerging as an important reliability challenge. Therefore, identifying and determining vulnerable points in the presence of fault has so important.Method: Traditional solutions based on redundancies are very expensive in terms of chip area, energy consumption, and performance. Consequently, providing low cost and efficient approaches to cope with SDCs has received researchers’ attention more than ever. Hence the lack of a high-precision method without fault injection becomes a research challenge. Utilizing fault injection methods in complex systems is costly; therefore, in identifying silent data corruptions, a method based on machine learning algorithm is used, which is not necessary to inject fault in all software. Multi-bit faults and silent data corruptions with instruction sources are also considered. For this goal, we have proposed the M5rule decision tree model to detect the silent data corruption error by calculating the importance of the instruction feature for the vulnerability. Then we have used the error detection method by copying the critical instructions with sort.Results: Finally, we evaluated our model on Mibench benchmarks with multiple test programs. The results show an overhead of 58 % with data silent corruption coverage rate of about 99%.Discussion: In order that we not only did the single-bit fault consider but also multiple-bit fault. In addition, fault had been injected into instruction and data. Consequently, the evaluation results show that our method achieves a better detection accuracy compared to other state-of-the-art methods.  Manuscript profile
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  2 - Dynamic Migration of SDN-based Switches to Distribute Control Layer Load and Increase Efficiency Using Ryu Controller
  neda abbasi Shiva Karimi
  20.1001.1.27832570.1401.3.4.2.6
  Introduction: Network needs in today's era include comprehensive improvement of communication and connections with more bandwidth, minimum delay and high throughput. Software-defined networking is one of the most promising modes of future Internet development due to the More

  Introduction: Network needs in today's era include comprehensive improvement of communication and connections with more bandwidth, minimum delay and high throughput. Software-defined networking is one of the most promising modes of future Internet development due to their centralized planning and management capabilities. The load balancing problem for distributed SDN controllers is one of the fundamental challenges of these networks, and a single centralized controller may cause reliability and scalability problems, and although several controllers can solve these problems, a flexibility mechanism is required for load balancing.Method:Therefore, in this research, a load balancing mechanism is proposed based on the load information strategy, so that each controller in the system periodically reports its load information to other controllers, and the overload controllers of the plan, load infomation They do not collect all other controllers before local decisions are made, which in turn reduces controller resource consumption. A load balancing strategy is proposed in the proposed response time-based scheme for multiple SDN controllers, which takes into account the real-time response time characteristics that change with the controller load. Another key part of the proposed scheme is that all these things are done in the Ryu controller by choosing an appropriate response time threshold and processing multiple overload controllers simultaneously, which can solve the load balancing problem of the SDN control panel of the overload controller well. slow This model proposes to transfer the management of specific switches between controllers.Results: In the simulation, the historical load and the future load of the switches were considered, and a switch migration algorithm with double weight was proposed, which led to a decrease in the frequency of switch migration. Experiments have proven that this scheme can quickly provide load balancing between controllers and reduce the number of switch migrations. The results showed that this design can lead to the migration of the overload controller and quickly reduce the workload of the overload controller. As a result, the proposed scheme can effectively achieve load balancing of multiple SDN controllers with high speed.  Manuscript profile
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  3 - A New Approach Based on Deep Learning Algorithms to Study Effective Factors of Using Social Networks on Students’ Performance
  Maryam Bakeshlo Mohammad Tahghighi Sharabyan
  20.1001.1.27832570.1401.3.4.3.7
  Introduction: In the past few years, the emerging technologies of mobile phones have grown rapidly and led to the creation of a new category of social media, which are very efficient mechanisms for collaboration and communication between their users. Social media consis More

  Introduction: In the past few years, the emerging technologies of mobile phones have grown rapidly and led to the creation of a new category of social media, which are very efficient mechanisms for collaboration and communication between their users. Social media consists of a variety of web-based tools that enable users to distribute and share new ideas, thoughts, and information in an interactive environment. Social networks and the use of these networks have become an inseparable part of the lives of many students, so it has a direct impact on all aspects of their lives, including academic performance. Therefore, in this research, a new approach based on data mining techniques will be presented to investigate the factors affecting the use of social networks in the academic performance of students, and for this purpose, the deep learning technique and classification will be used.Method: The proposed method has two main phases. In the first phase, the data is prepared for modeling during the three stages of data integration, cleaning, and transformation, and in the final phase, the data is modeled and analyzed using deep learning.Results: The presented method has a favorable output in the feature selection set with a value of 68%, which shows an improvement of 14% compared to the basic method, which can be concluded that about 68% of social networks and the use of the Internet on the learning and efficiency of students is effective.Discussion: Social networking sites are very useful in education and research considering that they are used in schools for organizational branding, recruiting, and encouraging students and employees to participate. In this research, a method to identify the impact of social networks and internet use on students' learning based on accurate classification has been presented. Manuscript profile
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  4 - Power Sharing Between Islanded Microgrid Inverters by Modifying the Droop Control Method
  kiomars sabzevari
  20.1001.1.27832570.1401.3.4.4.8
  Introduction: Distributed generation appears as the eco-friendly solution to a growing demand of electricity. Within the same idea, microgrids have become one of the most attractive sources of attention since they integrate local supply sources both with cleanliness and More

  Introduction: Distributed generation appears as the eco-friendly solution to a growing demand of electricity. Within the same idea, microgrids have become one of the most attractive sources of attention since they integrate local supply sources both with cleanliness and robustness. These microgrids can operate either connected to the utility grid, or on their own, namely the islanded mode. In the case of an island microgrid, how to control the DC bus voltage and the energy balance of the microgrid is necessary and essential for its use. Voltage and frequency control as well as active and reactive power sharing between distributed generation sources in island AC microgrids is one of the challenges of microgrid control. One of the control methods of islanded microgrids is to use the common droop control method. Although the droop control method can accurately divide the active power among distributed generation sources; But in the drop control method, reactive power sharing is not accurate.Method: In this article, the adaptive droop control method is used to compensate the voltage drop caused by the line impedance and increase the accuracy of reactive power sharing in the islanded microgrid. Communication between distributed generation sources is used to facilitate the adjustment of adaptive droop control during load changes. In the proposed method, there is an assurance that by cutting the connection between the scattered production sources, if the load does not change, the reactive power sharing will be done accurately. The proposed method has a better performance than the conventional droop control method.Results: The simulation of the proposed control method has been done using Simulink MATLAB. The simulation results show that the proposed control method has accurate reactive power sharing. And it has a better performance than the common drop method.Discussion: In the proposed control method, by compensating the impedance voltage drop of the transmission line to the common point of the units, the power sharing between the inverters is proportional to the capacity of the units. The simulation results show that reactive and active power division is performed accurately with the presence of a communication link between the units. In case of constant load and disconnection between the units, the power sharing between the units is accurate. In the case of disconnection of the communication link between inverters and load change, the proposed control method performs better than the conventional drop control method. Manuscript profile
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  5 - Sentiment Analysis of People’s opinion about Iranian National Cars with BERT
  Leila Gonbadi Niloofar Ranjbar
  20.1001.1.27832570.1401.3.4.5.9
  Introduction: With the development of the internet and social media, people have been actively discussing political and economic issues, and sharing their opinions online. The vast amount of data generated from these online discussions can be analyzed through text minin More

  Introduction: With the development of the internet and social media, people have been actively discussing political and economic issues, and sharing their opinions online. The vast amount of data generated from these online discussions can be analyzed through text mining methods to extract valuable information. One such method is aspect-based sentiment analysis, which allows for the analysis of people's opinions on various aspects of a topic. In this paper, we will focus on the analysis of people's opinions on the Iranian automobile industry and national cars using aspect-based sentiment analysis.Methodology: To achieve our goal, we first introduce a method for extracting different aspects related to national cars. We then use the "BERT" language model to extract vectors for different sentences related to the various aspects and finally use a neural network to classify the sentiments expressed in these sentences as positive, negative, or neutral.Results: The analysis of public opinions on various aspects of Iranian cars showed that the most discussed aspects were design, quality, and price. The sentiment expressed towards design was largely positive, with people expressing admiration for the unique and modern designs of Iranian cars. The sentiment expressed towards quality was mixed, with some people praising the improved quality of national cars, while others criticized the use of low-quality materials. The sentiment expressed towards price was largely negative, with people complaining about the high prices of Iranian cars compared to their foreign counterparts.Discussion: The results of our analysis provide valuable insights into the level of public satisfaction with various aspects of Iranian cars.  The mixed sentiment expressed towards the quality of Iranian cars highlights the need for manufacturers to focus on using high-quality materials to improve the overall quality of their products. The negative sentiment expressed toward the price of Iranian cars suggests that car manufacturers need to find ways to reduce production costs and offer more competitive pricing. In conclusion, aspect-based sentiment analysis can be used as an effective method to analyze public opinions on various aspects of a topic. Our analysis of public opinions on the Iranian automobile industry and national cars provides valuable insights for car manufacturers to improve the design, quality, and pricing of their products. By taking these insights into account, manufacturers can improve their performance and meet the needs and expectations of their customers. Manuscript profile
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  6 - Investigating the Effect of Changing the Distance between Nanomachines on Increasing the Efficiency of Message Delivery Using Chemotaxis and Network Connectivity Nano Communicative Bacteria
  Tayebe raiesi ardali vahid satari naeini javad mohammadzadeh
  20.1001.1.27832570.1401.3.4.6.0
  Introduction: Nanomolecular network is used as a new connection pattern in nanomachines. These connections are possible using biological components in the environment. The molecular communications have important drawbacks, such as very low capacity or the need to deploy More

  Introduction: Nanomolecular network is used as a new connection pattern in nanomachines. These connections are possible using biological components in the environment. The molecular communications have important drawbacks, such as very low capacity or the need to deploy a complex infrastructure. One of the most effective approaches for this purpose is using bacteria to carry encrypted message among nanomachines.Method: The current research examines effective routing in bacterial communication nano networks based on changing the distance between nanomachines. The aim of this research is to develop routing capability for bacterial communication nano networks. For this purpose, two intrinsic characteristics of bacteria, including chemotaxis and conjugation, have been used. In order to analyze the efficiency of message delivery, simulation was done for several different topologies. The purpose of simulation in different forms of topology is to investigate the effect of changing the distance between nanomachines and also the connection process in order to improve message delivery.Results: The results of this research showed that in the number of successful messages delivered to the destination for longer distances, it can be seen that topology 2 performs better. The comparison of the number of connections made at different distances for all three investigated topologies showed that with the increase in the number of bacteria in All three topologies increase the number of connections made, but in different intervals in terms of the distance between the nanomachines, it can be seen that the number of connections decreases as the distance increases due to the reduction of the effect field of the chemical adsorbent, which is needed to direct the movement of the bacteria.By examining and evaluating the simulation results for the average delay of the messages reached to the destination by changing the distance between the nanomachines, it can be seen that for all three topologies, with the increase in the number of bacteria, the average delay decreases, and with the increase in the distance between the nanomachines, the average delay also decreases. It can be seen that topology 2 has the lowest latency in terms of average latency for longer distances.Discussion: By increasing the distance among nanomachines, the number of received messages at the destination decreases as well. One of the topologies results in better average latency in longer distances compared to the others, because of the hollow center in this topology. Manuscript profile