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    Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran ( Scientific )
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    • Open Access Article

      1 - Presenting a Network-on-Chip Mapping Approach Based on Harmony Search Algorithm
      Zahra Bagheri Fatemeh Vardi Alireza Mahjoub
      Issue 2 , Vol. 21 , Summer 2023
      In network-on-chip implementation, mapping can be considered as an important step in application implementation. The tasks of an application are often represented in the form of a core graph. The cores establish a link between themselves using a communication platform a More
      In network-on-chip implementation, mapping can be considered as an important step in application implementation. The tasks of an application are often represented in the form of a core graph. The cores establish a link between themselves using a communication platform and often the network on the chip. For finding proper mapping for an application, developers have proposed various algorithms. In most cases, due to the complexity, exact search methods are used to find the mapping. However, these methods are suitable for networks with small dimensions. As the size of the network increases, the search time also increases exponentially. This article, from the perspective of a heuristic approach, uses the harmony search method to decide when to connect cores to routers. Our approach uses an improved version of the harmony search algorithm with a focus on reducing power consumption and delay. Algorithm complexity analysis reveals a more appropriate solution compared to similar algorithms with respect to application traffic pattern. Compared to similar methods, the algorithm achieves 39.98% less delay and 61.11% saving in power consumption. Manuscript profile

    • Open Access Article

      2 - Semantic Word Embedding Using BERT on the Persian Web
      shekoofe bostan Ali-Mohammad Zare-Bidoki mohamad reza pajohan
      Issue 2 , Vol. 21 , Summer 2023
      Using the context and order of words in sentence can lead to its better understanding and comprehension. Pre-trained language models have recently achieved great success in natural language processing. Among these models, The BERT algorithm has been increasingly popular More
      Using the context and order of words in sentence can lead to its better understanding and comprehension. Pre-trained language models have recently achieved great success in natural language processing. Among these models, The BERT algorithm has been increasingly popular. This problem has not been investigated in Persian language and considered as a challenge in Persian web domain. In this article, the embedding of Persian words forming a sentence was investigated using the BERT algorithm. In the proposed approach, a model was trained based on the Persian web dataset, and the final model was produced with two stages of fine-tuning the model with different architectures. Finally, the features of the model were extracted and evaluated in document ranking. The results obtained from this model are improved compared to results obtained from other investigated models in terms of accuracy compared to the multilingual BERT model by at least one percent. Also, applying the fine-tuning process with our proposed structure on other existing models has resulted in the improvement of the model and embedding accuracy after each fine-tuning process. This process will improve result in around 5% accuracy of the Persian web ranking. Manuscript profile

    • Open Access Article

      3 - Video Summarization Using a Clustering Graph Neural Networks
      Mahsa RahimiResketi Homayun Motameni Ebrahim Akbari Hossein  Nematzadeh
      Issue 2 , Vol. 21 , Summer 2023
      The increase of cameras nowadays, and the power of the media in people's lives lead to a staggering amount of video data. It is certain that a method to process this large volume of videos quickly and optimally becomes especially important. With the help of video summar More
      The increase of cameras nowadays, and the power of the media in people's lives lead to a staggering amount of video data. It is certain that a method to process this large volume of videos quickly and optimally becomes especially important. With the help of video summarization, this task is achieved and the film is summarized into a series of short but meaningful frames or clips. This study tried to cluster the data by an algorithm (K-Medoids) and then with the help of a convolutional graph attention network, temporal and graph separation is done, then in the next step with the connection rejection method, noises and duplicates are removed, and finally summarization is done by merging the results obtained from two different graphical and temporal steps. The results were analyzed qualitatively and quantitatively on three datasets SumMe, TVSum, and OpenCv. In the qualitative method, an average of 88% accuracy rate in summarization and 31% error rate was achieved, which is one of the highest accuracy rates compared to other methods. In quantitative evaluation, the proposed method has a higher efficiency than the existing methods. Manuscript profile

    • Open Access Article

      4 - Proposing a Detection and Mitigation Approach for DDoS Attacks on SDN-Based IoT Networks
      fatemeh MotieShirazi Seyedakbar Mostafavi
      Issue 2 , Vol. 21 , Summer 2023
      Internet of Things (IoT) is a network of objects on which objects can communicate with other objects. The Internet of Things is currently constantly under numerous attacks due to technical, legal and human problems. One of the most important of these attacks is the Deni More
      Internet of Things (IoT) is a network of objects on which objects can communicate with other objects. The Internet of Things is currently constantly under numerous attacks due to technical, legal and human problems. One of the most important of these attacks is the Denial of Service (DoS) attack, in which normal network services are out of service and it is impossible for objects and users to access the server and other resources. Existing security solutions have not been able to effectively prevent interruption attacks in Internet of Things services. Software-oriented network (SDN) is a new architecture in the network based on the separation of the control and data plane of the network. Programmability and network management capability by SDN can be used in IoT services because some IoT devices send data periodically and in certain time intervals. SDN can help reduce or prevent the data flood caused by IoT if properly deployed in the data center. In this article, a method to detect DDoS attacks in Internet of Things based on SDN is presented and then an algorithm to reduce DDoS attacks is presented. The proposed method is based on the entropy criterion, which is one of the most important concepts in information theory and is calculated based on the characteristics of the flow. In this method, by using two new components on the controller to receive incoming packets and considering the time window and calculating entropy and flow rate, a possible attack is detected in the network, and then based on the statistics of the flow received from the switches, the certainty of the attack is determined. Compared to the existing methods, the proposed method has improved 12% in terms of attack detection time and 26% in terms of false positives/negatives. Manuscript profile

    • Open Access Article

      5 - Ontology Matching Based on Maintaining Local Similarity of Information Using Propagation Technique
      NazarMohammad Parsa Asieh Ghanbarpour
      Issue 2 , Vol. 21 , Summer 2023
      In recent years, ontologies, as one of the most important components of the semantic web, have expanded in various fields. The problem of ontology matching has been raised with the aim of creating a set of mappings between entities of ontologies. This problem is classif More
      In recent years, ontologies, as one of the most important components of the semantic web, have expanded in various fields. The problem of ontology matching has been raised with the aim of creating a set of mappings between entities of ontologies. This problem is classified as an NP-hard problem. Therefore, greedy methods have been proposed to solve it in different ways. Selecting the appropriate lexical, structural and semantic similarity criteria and using an effective combination method to obtain the final mapping is one of the most important challenges of these methods. In this paper, an automatic method of matching ontologies is proposed to provide a one-to-one mapping set. This method detects primary mappings based on a new lexical similarity criterion, which is accordance with the descriptive essence of entities and combining this similarity with semantic similarity obtained from external semantic sources. By locally propagating the score of initial mappings in the class hierarchy graph, structurally matching entities are identified. In this method, property matching is examined in a separate step. In the final step, the mapping filter is applied in order to maintain the consistency of the final mapping set. In the evaluation section, comparing the performance of the lexical similarity measure compared to other proposed textual similarity measures, indicates the efficiency of this measure in the problem of ontology matching. In addition, the results of the proposed matching system compared to the results of the set of participating systems in the OAEI competitions shows this system in the second place and higher than many complex matching systems. Manuscript profile

    • Open Access Article

      6 - Distributed Primal-Dual Algorithm with Variable Parameters and Bidirectional Incremental Cooperation
      Ghanbar  Azarnia
      Issue 2 , Vol. 21 , Summer 2023
      Special conditions of wireless sensor networks, such as energy limitation, make it essential to accelerate the convergence of algorithms in this field, especially in the distributed compressive sensing (DCS) scenarios, which have a complex reconstruction phase. This pap More
      Special conditions of wireless sensor networks, such as energy limitation, make it essential to accelerate the convergence of algorithms in this field, especially in the distributed compressive sensing (DCS) scenarios, which have a complex reconstruction phase. This paper presents a DCS reconstruction algorithm that provides a higher convergence rate. The proposed algorithm is a distributed primal-dual algorithm in a bidirectional incremental cooperation mode where the parameters change with time. The parameters are changed systematically in the convex optimization problems in which the constraint and cooperation functions are strongly convex. The proposed method is supported by simulations, which show the higher performance of the proposed algorithm in terms of convergence rate, even in stricter conditions such as the small number of measurements or the lower degree of sparsity. Manuscript profile
    Most Viewed Articles

    • Open Access Article

      1 - Modeling and Reliability Evaluation of Magnetically Controlled Reactor based on the Markov Process Technique
      M. Haghshenas R. Hooshmand
      Issue 3 , Vol. 17 , Autumn 2019
      Controlled reactors as one of the flexible AC transmission systems play an important role in the availability and reliability of power systems.However, in the conventional reliability assessment of power systems, reactive power is considered only as a constraint for the More
      Controlled reactors as one of the flexible AC transmission systems play an important role in the availability and reliability of power systems.However, in the conventional reliability assessment of power systems, reactive power is considered only as a constraint for the network, and so far no precise model for assessing the reliability of reactors has been provided. In this paper, a new reliability model based on Markov process is proposed for a magnetically controlled reactor (MCR). In the modeling process, first the MCR structure is divided into two distinct parts, and then the extracted Markov models are combined based on frequency/duration technique.Since temperature changes play a significant role in changing the failure rate of electrical equipment, the effect of temperature changes in accordance with the MIL-217F standard has been considered in the proposed model and its impact on the probability of MCR operating modes has been evaluated. The simulation results have shown that in normal temperature conditions, the control system and at high temperatures, reactor windings can have the greatest impact on the availability of MCR. Comparison of reliability indices at different temperatures has shown that under different temperature conditions, different components will affect the availability of MCR. Therefore, in this condition, the measures needed to improve the reliability of the reactor can be different. This fact highlights the importance of considering the effect of operating temperature on reliability assessment as well as planning for preventive maintenance to improve the performance of reactive power sources. Manuscript profile

    • Open Access Article

      2 - Reactive Power Management in the Presence of Wind Turbine Considering Uncertainty of Load and Generation
      E.  Moharamy S. Esmaeili
      Issue 3 , Vol. 13 , Autumn 2015
      Reactive power management is very important in power systems for the secure transmission of active power, especially when a part of system generation is provided by stochastic sources like wind energy. This paper presents a new algorithm for reactive power management in More
      Reactive power management is very important in power systems for the secure transmission of active power, especially when a part of system generation is provided by stochastic sources like wind energy. This paper presents a new algorithm for reactive power management in the presence of wind generators and considering the stochastic nature of these sources and load simultaneously .In this regard, the proposed probabilistic algorithm, minimizes the overall cost function of the system considering the cost of each of the reactive power sources including wind generators. Besides economic issues, the voltage stability margin, having sufficient reactive power reserve in each area of voltage control and considering transmission congestion probability as technical aspects of the planning, have been investigated .Another advantage of this method compared to the previous one, is using of doubly-fed induction generator (DFIG) and its capability in providing reactive power considering the constraints of grid side and rotor side converters. The proposed optimization algorithm uses a multi objective function with different weighting coefficients. This algorithm is applied to minimize total reactive power, cost and losses and maximize voltage stability margin and reactive power reserve, simultaneously, meanwhile the probabilistic nature of wind and load forecasting inaccuracy is considered in this algorithm. The proposed method is implemented on the IEEE 30-bus test system and the simulation results demonstrate the effectiveness of proposed algorithm in real conditions for PMSMs against internal faults, especially inter-turn faults. Manuscript profile

    • Open Access Article

      3 - Modeling of K-250 Compressor Using NARX and Hierarchical Fuzzy Model
      Adel Khosravi Abbas  Chatraei G. Shahgholian Seyed-Mohamad Kargar
      Issue 3 , Vol. 18 , Autumn 2020
      Due to the increasing use of compressors in the industry, it is important to determine a mathematical model for the compressor to design a control system, analysis and simulation of the computer. Also, in recent years, smart modeling such as neural network and fuzzy net More
      Due to the increasing use of compressors in the industry, it is important to determine a mathematical model for the compressor to design a control system, analysis and simulation of the computer. Also, in recent years, smart modeling such as neural network and fuzzy network have been considered by researchers for their more realistic performance, and their types have been used for modeling. Smart methods have high capability to communicate between input and output data. In this paper, modeling of K-250 compressor at Isfahan smelter company based on smart models of fuzzy neural network is presented. The Nonlinear Auto Regressive With exogenous input (Narx) and hierarchical fuzzy network are presented. For modeling, the system has been tested and the input and output data of the compressor using compressor sensors and image processing are used to convert the data into the required data in the modeling, then the above algorithms of the compressor model will be achieved with the help of software, MATLAB. The results of modeling Which NARX performed better than hierarchical fuzzy. Among the two models presented in this paper, the NARX model shows a better response than the hierarchical fuzzy network in all cases and in all aspects of the performance criteria. Manuscript profile

    • Open Access Article

      4 - Design and Analysis of a Novel Robust and Fast Sliding-Mode Control with Multi-Slope Sliding Surface for Single-Phase Three Level NPC Inverters under Different Loads and Reduce the Output THD
      B. Khajeh-Shalaly G. Shahgholian
      Issue 2 , Vol. 15 , Summer 2017
      In this paper control structure with robust performance in presence of parametric uncertainties of the converter in order to improve pure sinusoidal inverter in whole functional and loading conditions is rendered. The controller guarantees fast and accurate behavior of More
      In this paper control structure with robust performance in presence of parametric uncertainties of the converter in order to improve pure sinusoidal inverter in whole functional and loading conditions is rendered. The controller guarantees fast and accurate behavior of the converter in order to increase the output voltage quality and reduce output harmonics. This controller by sliding performance and utilizing output voltage and capacitor current used in the control process, not only has exact output voltage tracking from reference but also has ability to reject the periodic disturbances due to loading. Also, it guides error states to zero rapidly and makes transient states of the converter as well as possible at error moments that is the same high spikes and loads in output current. Another characteristic of the proposed controller is, improved stability region under wide ranges of loading in different conditions. Accuracy of proposed controller on a single-phase three level NPC inverter which has high sensitivity in control in order to increase quality, decrease harmonics and THD output has been compared with a single-slope sliding mode controller with the sane loading conditions and reference. The simulations results are obtained by MATLAB. Manuscript profile

    • Open Access Article

      5 - Close Loop Identification for Combustion System by Recurrent Adaptive Neuro-Fuzzy Inference System and Network with Exogenous Inputs
      E. Aghadavoodi G. Shahgholian
      Issue 3 , Vol. 16 , Autumn 2018
      Boiler-turbine is a multi-variable and complicated system in steam power plants including combustion, temperature and drum water level. Selecting control loops as a unique loop in order to identify and control the boiler as a whole unit is a difficult and complicated ta More
      Boiler-turbine is a multi-variable and complicated system in steam power plants including combustion, temperature and drum water level. Selecting control loops as a unique loop in order to identify and control the boiler as a whole unit is a difficult and complicated task, because of nonlinear time variant dynamic characteristics of the boiler. It is necessary to identify each control group in order to accomplish a realistic and effective model, appropriate for designing an efficient controller. Both the effective and efficient performance of the identified model during the load change is of major importance. Here, not all parts of the system should be considered as a unit part, if determining and effective and realistic model is sought. The combustion loop of the 320 MW steam power plant of Islam Abad, Isfahan is the subject. Due to the sensitivity and complexity of the system, with respect to its nonlinear and closed loop characteristics, the identification of the system is conducted through intelligent procedures like recurrent adaptive neuro-fuzzy inference system (RANFIS) and nonlinear autoregressive model with exogenous input (NARX). The comparisons of the findings with actual data collected from the plant are presented and the accuracy of the procedures is determined. Manuscript profile

    • Open Access Article

      6 - Proposing a Density-Based Clustering Algorithm with Ability to Discover Multi-Density Clusters in Spatial Databases
      A. Zadedehbalaei A. Bagheri H.  Afshar
      Issue 3 , Vol. 15 , Autumn 2017
      Clustering is one of the important techniques for knowledge discovery in spatial databases. density-based clustering algorithms are one of the main clustering methods in data mining. DBSCAN which is the base of density-based clustering algorithms, besides its benefits s More
      Clustering is one of the important techniques for knowledge discovery in spatial databases. density-based clustering algorithms are one of the main clustering methods in data mining. DBSCAN which is the base of density-based clustering algorithms, besides its benefits suffers from some issues such as difficulty in determining appropriate values for input parameters and inability to detect clusters with different densities. In this paper, we introduce a new clustering algorithm which unlike DBSCAN algorithm, can detect clusters with different densities. This algorithm also detects nested clusters and clusters sticking together. The idea of the proposed algorithm is as follows. First, we detect the different densities of the dataset by using a technique and Eps parameter is computed for each density. Then DBSCAN algorithm is adapted with the computed parameters to apply on the dataset. The experimental results which are obtained by running the suggested algorithm on standard and synthetic datasets by using well-known clustering assessment criteria are compared to the results of DBSCAN algorithm and some of its variants including VDBSCAN, VMDBSCAN, LDBSCAN, DVBSCAN and MDDBSCAN. All these algorithms have been introduced to solve the problem of multi-density data sets. The results show that the suggested algorithm has higher accuracy and lower error rate in comparison to the other algorithms. Manuscript profile

    • Open Access Article

      7 - Automatic Reference Image Selecting for Histogram Matching in Image Enhancement
      N. Samadiani H. Hassanpour
      Issue 2 , Vol. 13 , Summer 2015
      In this paper, a method is proposed to automatically select reference image in histogram matching. Histogram matching is one of the simplest spatial image enhancement methods which improves contrast of the initial image based on histogram of the reference image. In the More
      In this paper, a method is proposed to automatically select reference image in histogram matching. Histogram matching is one of the simplest spatial image enhancement methods which improves contrast of the initial image based on histogram of the reference image. In the conventional histogram matching methods, user should perform several experiments on various images to find a suitable reference image. This paper presents a new method to automatically select the reference image. In this method, images are converted from RGB to HSV, and the illumination (V) components are considered to select the reference image. The appropriate reference image is selected using a similarity measure via measuring the similarity between the histograms of the initial image and histograms of the images in the data base. Indeed, an image with similar histogram to the histogram of the original images is more appropriate to choose as the reference image for histogram matching. Results in this research indicate superiority of the proposed approach, compared to other existing approaches, in image enhancement via histogram matching. In addition, the user would have no concern in selecting an appropriate reference image for histogram matching in the proposed approach. This approach is applicable to both RGB and gray scale images. Manuscript profile

    • Open Access Article

      8 - Design and Implementation of an IGBT Gate Driver with Necessary Protections and SMD Devices
      M. Fazeli S. A. Abrishamifar
      Issue 1 , Vol. 4 , Spring_Summer 2006
      The Gate drivers in modern power converters which use the power IGBT must be provide several main operations such as electrical isolation, current amplifying, and protection against overcurrent and overvoltage conditions. This paper describes such a new circuit which is More
      The Gate drivers in modern power converters which use the power IGBT must be provide several main operations such as electrical isolation, current amplifying, and protection against overcurrent and overvoltage conditions. This paper describes such a new circuit which is made using SMD devices suitable for driving the high and medium power IGBTs. This driver includes an isolated switching power supply, buffer circuits, and several protection circuits. It can operate by an input signal at TTL level and %50 duty cycle and is able to work up to 6A peak current. Manuscript profile

    • Open Access Article

      9 - Stochastic Planning of Resilience Enhancement for Electric Power Distribution Systems against Extreme Dust Storms
      M. Haghshenas R. Hooshmand M. Gholipour
      Issue 2 , Vol. 20 , Summer 2022
      Resilience in power systems refers to the system's ability to withstand severe disturbances with a low probability of occurrence. Because in recent years extreme dust storms have caused severe damage to Iran's electricity industry, especially in the south and southwest, More
      Resilience in power systems refers to the system's ability to withstand severe disturbances with a low probability of occurrence. Because in recent years extreme dust storms have caused severe damage to Iran's electricity industry, especially in the south and southwest, in this paper proposed a new scenario-based stochastic planning model for enhancement of power distribution systems resilience against extreme dust storms. In proposed model, in the first stage, the investment costs to improve the distribution system resilience against extreme dust storms are minimized due to the financial constraints, and in the second stage, the expected operating costs in dust storm conditions are minimized due to the operating constraints. Because network's insulation equipment are major cause of distribution system vulnerabilities in the dust storms, measures in the planning stage include replacement of porcelain insulators with silicon-rubber type, installation of automatic tie switches and installation of emergency generators. In the second stage, the measures are divided into preventive actions and corrective actions, and coordination between stages 1 and 2 is implemented in such a way that the results of each stage depend on the decision variables of the other stage. The simulation results for IEEE 33-bus test system and a 209 bus radial distribution network located in Khuzestan province, Iran, confirm the efficiency of the proposed model in different financial conditions. Manuscript profile

    • Open Access Article

      10 - Determination of Available Transfer Capability by Combined Method of Newton-Raphson-Seydel and Holomorphic Load Flow with Improved Matrix Calculations
      Mostafa Eidiani
      Issue 1 , Vol. 21 , Spring 2023
      This paper first demonstrates that high direct current lines will undoubtedly be the backbone of the future transmission network. The Newton Raphson Seydel alternating load flow equations are then combined with the direct current line equations. This paper employed matr More
      This paper first demonstrates that high direct current lines will undoubtedly be the backbone of the future transmission network. The Newton Raphson Seydel alternating load flow equations are then combined with the direct current line equations. This paper employed matrix techniques to increase the speed of solving problems as the dimensions of the equations get larger. Furthermore, the holomorphic load flow does not require an initial estimate to run the load flow, and if a solution exists, the precise answer is calculated. The initial guess of Newton Raphson Seydel was calculated using this approach. In this paper, we describe a novel approach that can compute the available transfer capability in small and large networks with sufficient accuracy and speed by combining these methods. The simulation in this paper uses five networks: 39 IEEE buses, 118 IEEE buses, 300 IEEE buses, 145 Iowa state buses, and 1153 East Iran buses network. In addition, four approaches were employed for comparison: continuous power flow, the general minimum residual method, Newton Raphson Seydel classical method, and the standard holomorphic power flow method. The results of the simulations suggest that the proposed strategy is acceptable. Manuscript profile
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    M. Ehsan (دانشگاه صنعتی شريف) R. Jalili (دانشگاه صنعتی شريف) Abdolhosein Rezaei (دانشگاه علم و فرهنگ) M. H. Savoji (دانشگاه شهید بهشتی) H. Seifi (دانشگاه تربیت مدرس) Mohammad Javad Shayeganfard (دانشگاه علم و فرهنگ) M. Shafiee (دانشگاه صنعتی امير کبير) Hamid Reza Sadegh Mohammadi (پژوهشکده برق جهاد دانشگاهی) A. Khaki Sedigh (دانشگاه صنعتی خواجه نصیرالدين طوسی) M. R. Aref (دانشگاه صنعتی شريف) M. Fathi (دانشگاه علم و صنعت ايران) M. K. Moravvej Farshi (دانشگاه تربيت مدرس)
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    Last Update 12/1/2023