University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Automatic and non-invasive method for Ischemic stroke detection using a novel time-frequency model of plantar pressure signals Automatic and non-invasive method for Ischemic stroke detection using a novel time-frequency model of plantar pressure signals 413 423 19099 10.22034/tjee.2025.63792.4900 FA Zahra Atrachali Faculty of Biomedical Engineering, Sahand University of Technology, Tabriz, Iran. Peyvand Ghaderyan Faculty of Biomedical Engineering, Sahand University of Technology, Tabriz, Iran. Journal Article 2024 10 01 The occurrence of stroke is due to the sudden degeneration of brain cells, which is caused by the lack of oxygen supply to the cells due to vascular blockage or their rupture and the interruption of blood flow, which can lead to gait impairement. The brain imaging techniques including magnetic resonance imaging, computed tomography and cerebral angiography are the main tools for stroke detection, which may not provide a cost-effective and non-invasive diagnosis. Tthis study aims to propose an automatic, non-invasive and low-cost method for Ischemic stroke detection based on computer-aided analysis of the plantar pressure signals. The proposed method is based on new time-frequency plantar feature extraction based on Tunable Q-factor Wavelet Transform, informative feature selection based on ReliefF and classification based on Support Vector Machine, K-Nearest Neighborhood and Random Forest techniques. The main property of this method is the ability to extract fluctuating components and transient information of non-stationary plantar pressure signal using a new time-frequency method and the possibility of adapting to its time-varying characteristics. In order to evaluate the detection performance, the foot pressure signals of 36 patients afflicted with stroke and 46 healthy controls recorded during walking has been used. The obtained results have shown the high diagnostic capability of the proposed method with an average accuracy rate of 99.77% using 35 simple statistical features. The proposed method is able to provide a trade-off between high diagnostic accuracy and low computational cost using simple statistical plantar features, which seems suitable for practical diagnostic applications. The occurrence of stroke is due to the sudden degeneration of brain cells, which is caused by the lack of oxygen supply to the cells due to vascular blockage or their rupture and the interruption of blood flow, which can lead to gait impairement. The brain imaging techniques including magnetic resonance imaging, computed tomography and cerebral angiography are the main tools for stroke detection, which may not provide a cost-effective and non-invasive diagnosis. Tthis study aims to propose an automatic, non-invasive and low-cost method for Ischemic stroke detection based on computer-aided analysis of the plantar pressure signals. The proposed method is based on new time-frequency plantar feature extraction based on Tunable Q-factor Wavelet Transform, informative feature selection based on ReliefF and classification based on Support Vector Machine, K-Nearest Neighborhood and Random Forest techniques. The main property of this method is the ability to extract fluctuating components and transient information of non-stationary plantar pressure signal using a new time-frequency method and the possibility of adapting to its time-varying characteristics. In order to evaluate the detection performance, the foot pressure signals of 36 patients afflicted with stroke and 46 healthy controls recorded during walking has been used. The obtained results have shown the high diagnostic capability of the proposed method with an average accuracy rate of 99.77% using 35 simple statistical features. The proposed method is able to provide a trade-off between high diagnostic accuracy and low computational cost using simple statistical plantar features, which seems suitable for practical diagnostic applications. https://tjee.tabrizu.ac.ir/article_19099_472d0a66169a647269e7a7b53c6e1bc7.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Effect of double vacancy defect position on the Zigzag Phosphorene Nanoribbon Tunneling FETs Effect of double vacancy defect position on the Zigzag Phosphorene Nanoribbon Tunneling FETs 425 433 19994 10.22034/tjee.2025.64781.4928 FA Hadi Owlia Department of Electrical Engineering, Faculty of Engineering, Ardakan University, P.O. Box 184, Ardakan, Iran Mohammad Bagher Nasrollahnejad Department of Electrical Engineering, Gorgan Branch, Islamic Azad University, Gorgan, Iran Journal Article 2024 12 03 In this study, the effect of the position of a double-vacancy defect on the electrical performance of phosphorene nanoribbon tunneling field-effect transistors (TFETs) with a zigzag edge has been investigated. By varying the defect position along the length and width of the transistor channel, it was observed that the presence of defects in six studied positions—three along the length ("near source", "center", and "near drain") and three along the width ("center", "in between" and "near edge")—leads to a reduction in the transistor's on/off current ratio. The best performance is observed in the structure where the defect is located at the "in between" position of the channel width, with an on/off current ratio of 1600. Furthermore, the cut-off frequency decreases in all cases, with the smallest reduction occurring when the defect is positioned at the "in between" and "near edge" locations along the channel width, amounting to less than 10%. The calculations were performed using the Slater-Koster quasi-empirical method with DFTB-CP2K parameters. These findings demonstrate that the position of the double-vacancy defect has a significant impact on the electrical performance of phosphorene nanoribbon TFETs and should be considered an important factor in the design and fabrication of such transistors. In this study, the effect of the position of a double-vacancy defect on the electrical performance of phosphorene nanoribbon tunneling field-effect transistors (TFETs) with a zigzag edge has been investigated. By varying the defect position along the length and width of the transistor channel, it was observed that the presence of defects in six studied positions—three along the length ("near source", "center", and "near drain") and three along the width ("center", "in between" and "near edge")—leads to a reduction in the transistor's on/off current ratio. The best performance is observed in the structure where the defect is located at the "in between" position of the channel width, with an on/off current ratio of 1600. Furthermore, the cut-off frequency decreases in all cases, with the smallest reduction occurring when the defect is positioned at the "in between" and "near edge" locations along the channel width, amounting to less than 10%. The calculations were performed using the Slater-Koster quasi-empirical method with DFTB-CP2K parameters. These findings demonstrate that the position of the double-vacancy defect has a significant impact on the electrical performance of phosphorene nanoribbon TFETs and should be considered an important factor in the design and fabrication of such transistors. https://tjee.tabrizu.ac.ir/article_19994_76167e2e75d7e7af782d47cc4c95a6ba.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Architectural Design and Hardware Implementation of Smoothing Filters in 3D Images Architectural Design and Hardware Implementation of Smoothing Filters in 3D Images 435 446 19834 10.22034/tjee.2025.66018.4970 FA Jalal Babaie Electrical Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran Alireza Behrad Electrical Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran Journal Article 2025 02 21 In recent years, 3D technologies have experienced significant growth and have impacted various fields such as robotics, entertainment, surveillance, and security. One of the critical processes in this domain is smoothing filters in 3D models. In this regard, this paper presents two fixed-point, parallel, and pipeline-based hardware architectures for two smoothing filters: the mean and Gaussian filters. In the proposed architecture, during the preprocessing stage, 3D image data is represented appropriately. Two different hardware architectures are proposed for the preprocessing stage. Additionally, two distinct hardware architectures are proposed for the mean and Gaussian filters, differing in the structure of 3D data representation during preprocessing. Furthermore, a lookup table method is used to compute the exponential function for the Gaussian filter. The proposed architectures are implemented using the Verilog hardware description language and simulated and synthesized using ISE and Vivado software. For a 3D image with 299 vertices and 562 faces, the operating frequency for the mean filter with coordinate and vector length structures is approximately 19 MHz, and the achieved processing rates are 37,367 and 28,081 images per second, respectively. For the Gaussian filter, the operating frequency is around 19 MHz, and the obtained processing rates are 37,299 and 28,336 images per second, respectively. In recent years, 3D technologies have experienced significant growth and have impacted various fields such as robotics, entertainment, surveillance, and security. One of the critical processes in this domain is smoothing filters in 3D models. In this regard, this paper presents two fixed-point, parallel, and pipeline-based hardware architectures for two smoothing filters: the mean and Gaussian filters. In the proposed architecture, during the preprocessing stage, 3D image data is represented appropriately. Two different hardware architectures are proposed for the preprocessing stage. Additionally, two distinct hardware architectures are proposed for the mean and Gaussian filters, differing in the structure of 3D data representation during preprocessing. Furthermore, a lookup table method is used to compute the exponential function for the Gaussian filter. The proposed architectures are implemented using the Verilog hardware description language and simulated and synthesized using ISE and Vivado software. For a 3D image with 299 vertices and 562 faces, the operating frequency for the mean filter with coordinate and vector length structures is approximately 19 MHz, and the achieved processing rates are 37,367 and 28,081 images per second, respectively. For the Gaussian filter, the operating frequency is around 19 MHz, and the obtained processing rates are 37,299 and 28,336 images per second, respectively. https://tjee.tabrizu.ac.ir/article_19834_fcefd7cd46fd53cf6748ac797506fbfd.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Data-Driven Fault-Tolerant Model Predictive Control with Online Adaptation Based on Dynamic Mode Decomposition Data-Driven Fault-Tolerant Model Predictive Control with Online Adaptation Based on Dynamic Mode Decomposition 447 457 18530 10.22034/tjee.2024.61220.4832 FA Mohammadhosein Bakhtiaridoust Department of Electrical and Computer Engineering, Qom University of Technology, Qom, Iran Meysam Yadegar Department of Electrical and Computer Engineering, Qom University of Technology, Qom, Iran Mohammad Hadi Rezaei Department of Electrical Engineering, Yazd University, Yazd, Iran Journal Article 2024 04 20 This paper introduces a new data-driven control method for handling faults in multi-input multi-output linear systems. In this fault-tolerant control approach, a virtual actuator based on model predictive control is designed, utilizing an adaptive model extracted from the system's dynamic modes. This extracted model is recursively updated and utilized to predict the states of the faulty system. The method considers the effect of faults in predictive controller predictions and minimizes this effect. The proposed method does not require knowledge of system equations and it is fully data-driven. Moreover, since it utilizes predictive controller for improving system performance in the presence of faults, it can impose constraints on control inputs. Furthermore, the method presented in this paper is designed based on a virtual actuator and can easily be augmented to closed-loop systems to enhance their performance in dealing with faults. Finally, the performance of the proposed control method is examined through a simulation example. This paper introduces a new data-driven control method for handling faults in multi-input multi-output linear systems. In this fault-tolerant control approach, a virtual actuator based on model predictive control is designed, utilizing an adaptive model extracted from the system's dynamic modes. This extracted model is recursively updated and utilized to predict the states of the faulty system. The method considers the effect of faults in predictive controller predictions and minimizes this effect. The proposed method does not require knowledge of system equations and it is fully data-driven. Moreover, since it utilizes predictive controller for improving system performance in the presence of faults, it can impose constraints on control inputs. Furthermore, the method presented in this paper is designed based on a virtual actuator and can easily be augmented to closed-loop systems to enhance their performance in dealing with faults. Finally, the performance of the proposed control method is examined through a simulation example. https://tjee.tabrizu.ac.ir/article_18530_2fa4c6cf5309c142c5bc182c3ac095fb.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 The integration of random dropout technique with deep recurrent neural networks for modeling the transient behavior of the digital phase-locked loop circuit in the 1 GHz range The integration of random dropout technique with deep recurrent neural networks for modeling the transient behavior of the digital phase-locked loop circuit in the 1 GHz range 459 467 18996 10.22034/tjee.2024.64162.4911 FA Hamideh Parsaeian Department of Electrical Engineering, Yazd University, Yazd, Iran Ali Moftakharzadeh Department of Electrical Engineering, Yazd University, Yazd, Iran Sayed Alireza Sadrossadat Department of Computer Engineering, Yazd University, Yazd, Iran Ali Mirvakili Department of Electrical Engineering, Yazd University, Yazd, Iran Journal Article 2024 10 26 In this paper, we investigate and model the transient behavior of a digital phase-locked loop (DPLL) clock recovery circuit using artificial neural networks. The circuit modeling in this study is performed using a deep recurrent neural network (RNN), which faced challenges such as overfitting. This issue led to a reduction in the accuracy of the proposed model and a mismatch with real-world data. To address this problem, the dropout technique was employed, which improved the model's performance by reducing its complexity, resulting in a more accurate model compared to the standard deep recurrent neural network models. Additionally, by utilizing a deep gated recurrent unit (GRU), the model error is significantly reduced by 80.32% compared to the Recurrent Neural Network (RNN) model, and the model's accuracy is remarkably improved. The Deep Gated Recurrent Unit not only enhances the model's accuracy but also improves its stability and generalization capability. This method, especially when compared to transistor-level models, provides a model 43.28 times faster, which is important for practical and industrial applications.<br />compared to the Recurrent Neural Network (RNN) model, and the model's accuracy is remarkably improved. The Deep Gated Recurrent Unit not only enhances the model's accuracy but also improves its stability and generalization capability. This method, especially when compared to transistor-level models, provides a model 43.28 times faster, which is important for practical and industrial applications. In this paper, we investigate and model the transient behavior of a digital phase-locked loop (DPLL) clock recovery circuit using artificial neural networks. The circuit modeling in this study is performed using a deep recurrent neural network (RNN), which faced challenges such as overfitting. This issue led to a reduction in the accuracy of the proposed model and a mismatch with real-world data. To address this problem, the dropout technique was employed, which improved the model's performance by reducing its complexity, resulting in a more accurate model compared to the standard deep recurrent neural network models. Additionally, by utilizing a deep gated recurrent unit (GRU), the model error is significantly reduced by 80.32% compared to the Recurrent Neural Network (RNN) model, and the model's accuracy is remarkably improved. The Deep Gated Recurrent Unit not only enhances the model's accuracy but also improves its stability and generalization capability. This method, especially when compared to transistor-level models, provides a model 43.28 times faster, which is important for practical and industrial applications.<br />compared to the Recurrent Neural Network (RNN) model, and the model's accuracy is remarkably improved. The Deep Gated Recurrent Unit not only enhances the model's accuracy but also improves its stability and generalization capability. This method, especially when compared to transistor-level models, provides a model 43.28 times faster, which is important for practical and industrial applications. https://tjee.tabrizu.ac.ir/article_18996_e1cd773d1dd70e6894caaf27ce5c42c6.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Providing of the Proposed Structure of the Starlink Satellite System to Provide Direct to Cell Connection Service for Iran Providing of the Proposed Structure of the Starlink Satellite System to Provide Direct to Cell Connection Service for Iran 469 480 19941 10.22034/tjee.2025.65579.4958 FA Pedram Hajipour Assistant Professor, Satellite Communication Group, Faculty of Communications Technology, ICT Research Institute, Tehran, Iran Roghieh Karimzadeh Baee Assistant Professor, Satellite Communication Group, Faculty of Communications Technology, ICT Research Institute, Tehran, Iran Leila Mohammadi Assistant Professor, Satellite Communication Group, Faculty of Communications Technology, ICT Research Institute, Tehran, Iran Hossein Samimi Associate Professor, Radio Communication Group, Faculty of Communications Technology, ICT Research Institute, Tehran, Iran Marzieh Ahmadi Assistant Professor, Satellite Communication Group, Faculty of Communications Technology, ICT Research Institute, Tehran, Iran Journal Article 2025 01 22 Today, most companies and satellite service providers are looking to increase the number of satellites in the form of a satellite constellation in order to expand the coverage area and ultimately increase the capacity in providing direct satellite-to-device communication services for terrestrial users. Meanwhile, the Starlink constellation with a larger number of launched and planned satellites capable of providing this service is more operational. For this purpose, in this research, the method of using the Starlink satellite constellation with 220 satellites in 22 orbital planes (10 satellites in each plane) to provide this type of service in Iran has been studied. To examine the performance of Starlink, parameters such as the number of accesses, service duration, coverage, achievable capacity, and accessibility have been examined for the country of Iran, and specifically the city of Tehran. Finally, considering the use of the same frequency bands of the two types of Starlink and AST 2000 MHz satellites, the possible interferences of these two satellites have been investigated in terms of the cumulative distribution function in the short-term and long-term scenarios, as well as the amount of temperature changes in the receiver compared to the initial temperature. Today, most companies and satellite service providers are looking to increase the number of satellites in the form of a satellite constellation in order to expand the coverage area and ultimately increase the capacity in providing direct satellite-to-device communication services for terrestrial users. Meanwhile, the Starlink constellation with a larger number of launched and planned satellites capable of providing this service is more operational. For this purpose, in this research, the method of using the Starlink satellite constellation with 220 satellites in 22 orbital planes (10 satellites in each plane) to provide this type of service in Iran has been studied. To examine the performance of Starlink, parameters such as the number of accesses, service duration, coverage, achievable capacity, and accessibility have been examined for the country of Iran, and specifically the city of Tehran. Finally, considering the use of the same frequency bands of the two types of Starlink and AST 2000 MHz satellites, the possible interferences of these two satellites have been investigated in terms of the cumulative distribution function in the short-term and long-term scenarios, as well as the amount of temperature changes in the receiver compared to the initial temperature. https://tjee.tabrizu.ac.ir/article_19941_1c8653d0f440f95e48e9fcbaf086a31e.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Resource Allocation in Open Radio Access Networks (O-RANs): A Correlated Equilibrium Game Theoretic Approach Resource Allocation in Open Radio Access Networks (O-RANs): A Correlated Equilibrium Game Theoretic Approach 481 492 19440 10.22034/tjee.2025.60724.4814 FA Mahbod Hamzeh School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran. Vesal Hakami School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran. Journal Article 2024 02 26 Radio access network (RAN) provides integrated wireless communication between user devices and the core network as an interface. Open Radio Access Network (O-RAN) is an updated model of RAN design, similar to cloud RAN (C-RAN) and virtualized RAN (vRAN). In addition to finer-grained disaggregation features in network functions and the use of general-purpose server architecture, O-RAN benefits from the use of smart controllers, making it more suitable for 5G and 6G networks. Consequently, resource allocation in O-RAN requires different approaches. Controllers in O-RAN are categorized into Near-Real-Time (Near-RT) and Non-Real-Time (Non-RT) types, where the former utilizes applications called xApps and the latter uses applications called rApps to manage network resources. In this paper, we address the problem of joint allocation of open radio units (O-RUs) to users and sub-channels to O-RUs under uncertain and time-varying channel quality conditions. We formulate the problem using Markov modulated games and propose a multi-agent tracking equilibrium algorithm to achieve convergence and track the stable operating point of the network. Furthermore, through simulations, the efficiency of the proposed method is compared and evaluated against previous related solutions. Radio access network (RAN) provides integrated wireless communication between user devices and the core network as an interface. Open Radio Access Network (O-RAN) is an updated model of RAN design, similar to cloud RAN (C-RAN) and virtualized RAN (vRAN). In addition to finer-grained disaggregation features in network functions and the use of general-purpose server architecture, O-RAN benefits from the use of smart controllers, making it more suitable for 5G and 6G networks. Consequently, resource allocation in O-RAN requires different approaches. Controllers in O-RAN are categorized into Near-Real-Time (Near-RT) and Non-Real-Time (Non-RT) types, where the former utilizes applications called xApps and the latter uses applications called rApps to manage network resources. In this paper, we address the problem of joint allocation of open radio units (O-RUs) to users and sub-channels to O-RUs under uncertain and time-varying channel quality conditions. We formulate the problem using Markov modulated games and propose a multi-agent tracking equilibrium algorithm to achieve convergence and track the stable operating point of the network. Furthermore, through simulations, the efficiency of the proposed method is compared and evaluated against previous related solutions. https://tjee.tabrizu.ac.ir/article_19440_5cb2e3a08e5f1d6c098196a782827ed4.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Reconfigurable Microwave Polarizer and Ultra-‌Broadband THz Absorber Using Graphene-Quartz-Graphene Structure: Analysis and Design Reconfigurable Microwave Polarizer and Ultra-‌Broadband THz Absorber Using Graphene-Quartz-Graphene Structure: Analysis and Design 493 504 19098 10.22034/tjee.2025.62907.4875 FA Mahmood Rafaei-Booket Faculty of Electrical and Computer Engineering, University of Zanjan, Zanjan, Iran. Mahdieh Bozorgi Faculty of Electrical and Computer Engineering, University of Zanjan, Zanjan, Iran. 0000-0001-9663-2421 Journal Article 2024 08 11 An analytical aproach is presented to solve the problem of an obliquley plane-wave impinging on two sheets of biased-graphene with a static electromagnetic fields for providing physical insight into the graphene anisotropy. It is firstly shown that anisotropic behavior of surface conductivity of a biased-graphene sheet can be modeled by Drude model form. Using such a model, an analysis of the plane-wave diffraction by a graphene-quartz-graphene structure is developed for various incident angles of TE and TM polarizations. The reflection and transmission coefficients of such a structure are calculated for different values of graphene’s chemical potential and thickness of substrate. By studying the calculated results, it is found that using such a structure leads to polarization rotation of the incident plane-wave. This rotation angle for TM-polarized plane-waves is larger than TE-polarized ones once the incident wave is obliqulely impinging on such a structure. Finally, by proposing a new unit cell and changing the chemical potential of graphene sheets, an ultra-broadband (>190%) and tunable absorber is designed and numerically simulated within 0.1~7THz. It is shown that the proposed absorber has an excellent performance (absorbitivity > 80%) for both TE- and TM-polarized obliquley incident plane-waves once the incidence angle < 80^o An analytical aproach is presented to solve the problem of an obliquley plane-wave impinging on two sheets of biased-graphene with a static electromagnetic fields for providing physical insight into the graphene anisotropy. It is firstly shown that anisotropic behavior of surface conductivity of a biased-graphene sheet can be modeled by Drude model form. Using such a model, an analysis of the plane-wave diffraction by a graphene-quartz-graphene structure is developed for various incident angles of TE and TM polarizations. The reflection and transmission coefficients of such a structure are calculated for different values of graphene’s chemical potential and thickness of substrate. By studying the calculated results, it is found that using such a structure leads to polarization rotation of the incident plane-wave. This rotation angle for TM-polarized plane-waves is larger than TE-polarized ones once the incident wave is obliqulely impinging on such a structure. Finally, by proposing a new unit cell and changing the chemical potential of graphene sheets, an ultra-broadband (>190%) and tunable absorber is designed and numerically simulated within 0.1~7THz. It is shown that the proposed absorber has an excellent performance (absorbitivity > 80%) for both TE- and TM-polarized obliquley incident plane-waves once the incidence angle < 80^o https://tjee.tabrizu.ac.ir/article_19098_27dc4794da85ea4425720343c4e78d92.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Doherty Power Amplifier Linearity Improvement Using Internal Feed-Forward Network Doherty Power Amplifier Linearity Improvement Using Internal Feed-Forward Network 505 514 18896 10.22034/tjee.2024.61913.4856 FA Siamak Salmani Faculty of Electrical Engineering, University of Science and Technology, Tehran, Iran Majid Tayarani Faculty of Electrical Engineering, University of Science and Technology, Tehran, Iran Razieh Narimani Faculty of Electrical Engineering, University of Science and Technology, Tehran, Iran Journal Article 2024 06 01 The continuous expansion of telecommunication systems has led to more complex design of devices. One of the most important of these devices, which is usually considered as the last stage of the transmitter before the antenna, is the power amplifier, and one of these design complications is the need for more linearity in the power amplifier and high efficiency at the same time. There are various methods to improve the linearity of amplifiers, but usually, the higher the linearity improvement, the more complex it is, and the efficiency usually decreases. Meanwhile, the design of the amplifier itself is complicated. One of the suitable methods to improve the linearity of the amplifier, which also increases the efficiency at the same time, is the Doherty structure. Different structures of Doherty arrangement have been investigated, which create different properties. In this paper, a new arrangement for the Doherty structure is presented, which gives a great improvement in linearity and at the same time has high efficiency. This arrangement is a combination of doherty and forward structure and its adjustment can be done easily. The continuous expansion of telecommunication systems has led to more complex design of devices. One of the most important of these devices, which is usually considered as the last stage of the transmitter before the antenna, is the power amplifier, and one of these design complications is the need for more linearity in the power amplifier and high efficiency at the same time. There are various methods to improve the linearity of amplifiers, but usually, the higher the linearity improvement, the more complex it is, and the efficiency usually decreases. Meanwhile, the design of the amplifier itself is complicated. One of the suitable methods to improve the linearity of the amplifier, which also increases the efficiency at the same time, is the Doherty structure. Different structures of Doherty arrangement have been investigated, which create different properties. In this paper, a new arrangement for the Doherty structure is presented, which gives a great improvement in linearity and at the same time has high efficiency. This arrangement is a combination of doherty and forward structure and its adjustment can be done easily. https://tjee.tabrizu.ac.ir/article_18896_9f5f03c400feaf054ac6f40fa3eaf266.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Control and Protection of The Droop-Controlled Grid-Connected Solar Inverter with The Ability of Low Voltage Ride-Through Control and Protection of The Droop-Controlled Grid-Connected Solar Inverter with The Ability of Low Voltage Ride-Through 515 525 18532 10.22034/tjee.2024.61633.4846 FA Abdolhossein Saleh Electrical Engineering Department, Malayer University, Malayer, Iran Journal Article 2024 05 15 In this paper a new control scheme is proposed to protect the two-stage grid-connected solar inverter with ability of balanced Low Voltage Ride-Through (LVRT). In the proposed scheme, the power injection to the grid is regulated by controlling the voltage/frequency produced by the inverter. In the grid voltage drop condition , the solar inverter has the ability to inject reactive power into the grid in proportion to the voltage drop magnitude, and the inverter output voltage reference is determined by the droop control. To limit the inverter output current in the grid voltage drop condition, with the aim of maintaining the stability, an modified floating voltage drop characteristic has been proposed. Also, in the proposed scheme, a new integrated power tracking algorithm is presented, which in addition to tracking the maximum power in normal conditions, in the drop voltage conditions, if there is no empty capacity in the inverter to inject reactive power, it reduces the received power from the solar cells to allows the inverter to be protected against excessive current increase. The efficiency of the proposed method is shown by the time domain simulation in the MATLAB/SIMULINK environment and implementation in the way of processor in the loop In this paper a new control scheme is proposed to protect the two-stage grid-connected solar inverter with ability of balanced Low Voltage Ride-Through (LVRT). In the proposed scheme, the power injection to the grid is regulated by controlling the voltage/frequency produced by the inverter. In the grid voltage drop condition , the solar inverter has the ability to inject reactive power into the grid in proportion to the voltage drop magnitude, and the inverter output voltage reference is determined by the droop control. To limit the inverter output current in the grid voltage drop condition, with the aim of maintaining the stability, an modified floating voltage drop characteristic has been proposed. Also, in the proposed scheme, a new integrated power tracking algorithm is presented, which in addition to tracking the maximum power in normal conditions, in the drop voltage conditions, if there is no empty capacity in the inverter to inject reactive power, it reduces the received power from the solar cells to allows the inverter to be protected against excessive current increase. The efficiency of the proposed method is shown by the time domain simulation in the MATLAB/SIMULINK environment and implementation in the way of processor in the loop https://tjee.tabrizu.ac.ir/article_18532_331566dbc480824b034446c2de6219e9.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Automatic Classification of SSVEP Responses with Limited Training Samples and Shrinkage-Based Regularized Covariance Matrix Automatic Classification of SSVEP Responses with Limited Training Samples and Shrinkage-Based Regularized Covariance Matrix 527 538 18658 10.22034/tjee.2024.63151.4887 FA Alireza Talesh Jafadideh School of Engineering Science, College of Engineering, University of Tehran, Tehran, Iran Asghar Zarei Biomedical Engineering Faculty, Sahand University of Technology, Tabriz, Iran Journal Article 2024 08 27 A major hurdle in brain computer interface (BCI) development is the low information transfer rate (ITR). Using a short stimulation time is a solution that offers the advantages of increasing the ITR value and reducing the mental fatigue of users. When using short stimulation time, algorithms based on linearly constrained minimum variance beamforming (LCMV) provide better performance over other classifiers. However, their performance in aforementioned condition is still low due to the ill-conditioned estimation of the data covariance matrix. To address this problem, this study proposes the use of four Shrinkage-based regularized covariance matrices, including convex combination (CC), generalized linear combination (GLC), modified CC (MCC), and modified GLC (MGLC). The proposed covariance matrices are applied in the spatial-temporal beamformer LCMVst to construct a better weight vector, thereby improving the classification performance. The results showed that when using the shortest stimulation time (0.25s), the proposed beamformers LCMVst-CC, LCMVst-GLC, LCMVst-MCC, and LCMVst-MGLC provided a significant improvement of about 27% in average classification accuracy over conventional LCMVst. Also, the LCMVst-MCC and LCMVst-MGLC methods compared to LCMVst-CC and LCMVst-GLC methods provided approximately 9% improvement in classification accuracy. The results of this study show that the proposed beamformers have high potential in the development of SSVEP-based BCI systems. A major hurdle in brain computer interface (BCI) development is the low information transfer rate (ITR). Using a short stimulation time is a solution that offers the advantages of increasing the ITR value and reducing the mental fatigue of users. When using short stimulation time, algorithms based on linearly constrained minimum variance beamforming (LCMV) provide better performance over other classifiers. However, their performance in aforementioned condition is still low due to the ill-conditioned estimation of the data covariance matrix. To address this problem, this study proposes the use of four Shrinkage-based regularized covariance matrices, including convex combination (CC), generalized linear combination (GLC), modified CC (MCC), and modified GLC (MGLC). The proposed covariance matrices are applied in the spatial-temporal beamformer LCMVst to construct a better weight vector, thereby improving the classification performance. The results showed that when using the shortest stimulation time (0.25s), the proposed beamformers LCMVst-CC, LCMVst-GLC, LCMVst-MCC, and LCMVst-MGLC provided a significant improvement of about 27% in average classification accuracy over conventional LCMVst. Also, the LCMVst-MCC and LCMVst-MGLC methods compared to LCMVst-CC and LCMVst-GLC methods provided approximately 9% improvement in classification accuracy. The results of this study show that the proposed beamformers have high potential in the development of SSVEP-based BCI systems. https://tjee.tabrizu.ac.ir/article_18658_8176fddc2579643c9350da739b5a33ba.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Transformer hot spot temperature estimation with OFWF cooling using grey wolf algorithm Transformer hot spot temperature estimation with OFWF cooling using grey wolf algorithm 539 546 19305 10.22034/tjee.2025.60830.4819 FA Hadi Abbasi Faculty of Technical and Engineering, Imam Khomeini International University, Qazvin, Iran Mohammad Ali Taghikhani Faculty of Technical and Engineering, Imam Khomeini International University, Qazvin, Iran Journal Article 2024 03 07 Transformers are one of the most important and expensive components of the power network. The importance of corect operation of transformer is such that sustainable electricity supply for the consumer and increasing the reliability of the power grid without transformer health is not possible. Transformer health requires careful planning for them. Transformer hot spot temperature(HST) needs to be calculated for accurate transformer planning. Today, very large transformers are made that conventional cooling methods are not efficient for them. Therefore, it is necessary to use newer and more efficient cooling methods. Oil forced - water forced (OFWF) cooling has been less considered from engineers, designers and researchers. This cooling method despite high efficiency has received less attention from researchers. The use of heuristic algorithms for transformer HST estimation, regardless of their high efficiency, accuracy and appropriate speed have been less considered by investigators, therefore in this paper, in order to increase the accuracy of the transformer HST estimation, the grey wolf optimization(GWO) algorithm is used. This algorithm requires less memory to perform optimization calculations, on the other hand has high run speed and accuracy for optimization. Moreover, in order to increase the accuracy of the transformer HST estimation, dynamic model is used. The results show that the GWO algorithm increases speed and accuracy of the transformer HST estimation. Furthermore, the results indicate that the OFWF cooling method is very efficient for large power transformers. Transformers are one of the most important and expensive components of the power network. The importance of corect operation of transformer is such that sustainable electricity supply for the consumer and increasing the reliability of the power grid without transformer health is not possible. Transformer health requires careful planning for them. Transformer hot spot temperature(HST) needs to be calculated for accurate transformer planning. Today, very large transformers are made that conventional cooling methods are not efficient for them. Therefore, it is necessary to use newer and more efficient cooling methods. Oil forced - water forced (OFWF) cooling has been less considered from engineers, designers and researchers. This cooling method despite high efficiency has received less attention from researchers. The use of heuristic algorithms for transformer HST estimation, regardless of their high efficiency, accuracy and appropriate speed have been less considered by investigators, therefore in this paper, in order to increase the accuracy of the transformer HST estimation, the grey wolf optimization(GWO) algorithm is used. This algorithm requires less memory to perform optimization calculations, on the other hand has high run speed and accuracy for optimization. Moreover, in order to increase the accuracy of the transformer HST estimation, dynamic model is used. The results show that the GWO algorithm increases speed and accuracy of the transformer HST estimation. Furthermore, the results indicate that the OFWF cooling method is very efficient for large power transformers. https://tjee.tabrizu.ac.ir/article_19305_2a99954561ae947f089edd6f8599d5a2.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 High-Stability and Cost-effective Ultra High Step-Up DC-DC Converter for Solar-Powered DC Microgrids High-Stability and Cost-effective Ultra High Step-Up DC-DC Converter for Solar-Powered DC Microgrids 547 559 19886 10.22034/tjee.2025.66169.4979 FA Hamed Abdi Department of Electrical and Computer Engineering, Tabriz University, Tabriz, Iran. Naghi Rostami Department of Electrical and Computer Engineering, Tabriz University, Tabriz, Iran. Ali Nadermohammadi Department of Electrical and Computer Engineering, Tabriz University, Tabriz, Iran. Journal Article 2025 03 02 In solar-powered DC microgrids, utilization of a high-voltage-gain and stable DC-DC converter is essential. This paper proposes an ultra-high step-up DC-DC converter by combining voltage-boosting structures, an improved switched-capacitor (SC) cell, and a three-winding coupled inductor. The proposed converter not only achieves ultra-high voltage gain but also features low voltage stress on semiconductor elements, continuous input current with minimal ripple, low cost, high power density, common ground between input and output, and high efficiency. Additionally, the application of the pole placement control strategy and the appropriate positioning of system poles enhance the converter’s stability. A detailed analysis of the proposed converter is provided, covering its operational principles, mathematical derivations, and element design. A comparative evaluation is conducted based on key performance criteria for DC microgrids and solar energy systems, demonstrating the advantages of the proposed topology. Finally, a 200 W experimental prototype is developed to validate the theoretical findings, and the corresponding results are presented. In solar-powered DC microgrids, utilization of a high-voltage-gain and stable DC-DC converter is essential. This paper proposes an ultra-high step-up DC-DC converter by combining voltage-boosting structures, an improved switched-capacitor (SC) cell, and a three-winding coupled inductor. The proposed converter not only achieves ultra-high voltage gain but also features low voltage stress on semiconductor elements, continuous input current with minimal ripple, low cost, high power density, common ground between input and output, and high efficiency. Additionally, the application of the pole placement control strategy and the appropriate positioning of system poles enhance the converter’s stability. A detailed analysis of the proposed converter is provided, covering its operational principles, mathematical derivations, and element design. A comparative evaluation is conducted based on key performance criteria for DC microgrids and solar energy systems, demonstrating the advantages of the proposed topology. Finally, a 200 W experimental prototype is developed to validate the theoretical findings, and the corresponding results are presented. https://tjee.tabrizu.ac.ir/article_19886_033a4a3dd1284d46699be4dae996c36e.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 "Introducing a novel method for reducing coupling between range and angles in SIAR based on frequency coding in a circular array." "Introducing a novel method for reducing coupling between range and angles in SIAR based on frequency coding in a circular array." 561 569 17960 10.22034/tjee.2024.55812.4603 FA Reza Fatemi Mofrad Department of Electrical Engineering, Malek-Ashtar University of Technology, Tehran, Iran. Ghasem Asadi Department of Electrical Engineering, Malek-Ashtar University of Technology, Tehran, Iran. Journal Article 2023 04 16 The Synthetic Impulse and Aperture Radar (SIAR) are radars that have characteristics such as the ability to detect low RCS targets, Low Probability Of Intercept , resistance to anti-radiation missiles, and simultaneous detection and tracking of multiple targets. In these radars, one of the most important challenges is coupling between range and angle. This means that range error causes angle error and vice versa. To address this issue, radar designers typically design transmitting waveforms based on carrier frequency coding techniques In the past, sequential carrier frequency coding, positive and the negative sequential carrier frequency coding and random carrier frequency coding have been proposed to reduce the coupling between range and angle for a linear array(2D). In this article, geometrical and mathematical equations of coupling are presented for a circular array(3D) and a new method called as positive and negative random carrier frequency coding is proposed. It will be shown that proposed method reduces coupling and side lobe level by about 40% more than the previous frequency coding methods. Moreover, we provide evidence that the coupling between azimuth and elevation angles remains consistent across different frequency coding techniques. Furthermore, the random change of carrier frequency coding from one transmit period to the next allows us to leverage pulse-to-pulse frequency agility, adding an additional advantage to this method The Synthetic Impulse and Aperture Radar (SIAR) are radars that have characteristics such as the ability to detect low RCS targets, Low Probability Of Intercept , resistance to anti-radiation missiles, and simultaneous detection and tracking of multiple targets. In these radars, one of the most important challenges is coupling between range and angle. This means that range error causes angle error and vice versa. To address this issue, radar designers typically design transmitting waveforms based on carrier frequency coding techniques In the past, sequential carrier frequency coding, positive and the negative sequential carrier frequency coding and random carrier frequency coding have been proposed to reduce the coupling between range and angle for a linear array(2D). In this article, geometrical and mathematical equations of coupling are presented for a circular array(3D) and a new method called as positive and negative random carrier frequency coding is proposed. It will be shown that proposed method reduces coupling and side lobe level by about 40% more than the previous frequency coding methods. Moreover, we provide evidence that the coupling between azimuth and elevation angles remains consistent across different frequency coding techniques. Furthermore, the random change of carrier frequency coding from one transmit period to the next allows us to leverage pulse-to-pulse frequency agility, adding an additional advantage to this method https://tjee.tabrizu.ac.ir/article_17960_f8ee918e3f669f92f8f6264e88ac970f.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Brain Tissue Segmentation Using Conditional Spatial Gustafson-Kessel Clustering Brain Tissue Segmentation Using Conditional Spatial Gustafson-Kessel Clustering 571 582 19463 10.22034/tjee.2025.64184.4912 FA Ali Fahmi Jafargholkhanloo Assistant Professor, Department of Engineering Sciences, Faculty of Advanced Technologies, University of Mohaghegh Ardabili, Namin, Iran. Mousa Shamsi Professor, Faculty of Biomedical Engineering, Sahand University of Technology, Tabriz, Iran Mehdi Bashiri Bawil PhD Student, Faculty of Biomedical Engineering, Sahand University of Technology, Tabriz, Iran Journal Article 2024 10 26 The segmentation of brain tissues is a crucial step in evaluating morphological changes in various brain regions for the identification of different diseases. This process is influenced by factors such as noise and intensity non-uniformity. Fuzzy c-means clustering (FCM) is a widely used method for image segmentation but is sensitive to noise, and its convergence rate is affected by data distribution. FCM-based approaches typically use Euclidean distance for clustering, assuming a spherical distribution of data, which overlooks distance variations in similar and compact clusters. Additionally, varying levels of intensity non-uniformity can impact clustering performance. To address these limitations, this study presents the Conditional Spatial Gustafson-Kessel (CSGK) algorithm, which performs well in segmenting compact clusters such as cerebrospinal fluid (CSF) by considering data distribution in an elliptical space. The robustness of the conventional Gustafson-Kessel algorithm is enhanced by incorporating both local and global spatial information into a weighted membership function. Furthermore, a Wiener filter combined with wavelet transform (WFWT) is applied during preprocessing to reduce the sensitivity of input data to intensity non-uniformity. Experimental results demonstrate that CSGK is an accurate algorithm for segmenting multiple brain tissues across different levels of noise and intensity non-uniformity. The segmentation of brain tissues is a crucial step in evaluating morphological changes in various brain regions for the identification of different diseases. This process is influenced by factors such as noise and intensity non-uniformity. Fuzzy c-means clustering (FCM) is a widely used method for image segmentation but is sensitive to noise, and its convergence rate is affected by data distribution. FCM-based approaches typically use Euclidean distance for clustering, assuming a spherical distribution of data, which overlooks distance variations in similar and compact clusters. Additionally, varying levels of intensity non-uniformity can impact clustering performance. To address these limitations, this study presents the Conditional Spatial Gustafson-Kessel (CSGK) algorithm, which performs well in segmenting compact clusters such as cerebrospinal fluid (CSF) by considering data distribution in an elliptical space. The robustness of the conventional Gustafson-Kessel algorithm is enhanced by incorporating both local and global spatial information into a weighted membership function. Furthermore, a Wiener filter combined with wavelet transform (WFWT) is applied during preprocessing to reduce the sensitivity of input data to intensity non-uniformity. Experimental results demonstrate that CSGK is an accurate algorithm for segmenting multiple brain tissues across different levels of noise and intensity non-uniformity. https://tjee.tabrizu.ac.ir/article_19463_fd85ad05d1a34ebb6924f8457e951531.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Comparison of Decomposition Methods in Solving the Voltage and Reactive Power Control Problem in Multi-Area Power Systems Comparison of Decomposition Methods in Solving the Voltage and Reactive Power Control Problem in Multi-Area Power Systems 583 593 18531 10.22034/tjee.2024.61445.4844 FA Sajad Mehrabi Faculty of Electrical Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran. Farid Karbalaei Faculty of Electrical Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran. Journal Article 2024 05 08 Due to the limitations that exist in the centralized control method, nowadays mainly distributed methods are used to solve the problem of optimal power flow in multi-area power systems. In distributed methods, each area solves its optimization problem by coordinating the neighboring areas, but completely independently, that is, the optimization problem is divided into several sub-problems. In this article, three decomposition methods, namely the adjustment at the dummy boundary bus method, the exchange of adjacent boundary variables method and the coordination method by the power of the tie line, to solve the problem of control of voltage and reactive power in multi-area power systems, are introduced and compared with each other and with the centralized method. The common point of these three methods is that they all use the Lagrange relaxation method to remove complex constraints. Examining the simulation results shows that the adjustment at the dummy boundary bus requires more iterations than the other two methods to achieve convergence, but the results of this method are closer to the results of the centralized solution method, its means, this method has lower sub-optimally. Also, unlike the centralized method that requires a lot of information exchange, the decomposition methods are less dependent on the exchange of information between areas, and among them, the method of adjustment at the dummy boundary bus requires the least exchange. Due to the limitations that exist in the centralized control method, nowadays mainly distributed methods are used to solve the problem of optimal power flow in multi-area power systems. In distributed methods, each area solves its optimization problem by coordinating the neighboring areas, but completely independently, that is, the optimization problem is divided into several sub-problems. In this article, three decomposition methods, namely the adjustment at the dummy boundary bus method, the exchange of adjacent boundary variables method and the coordination method by the power of the tie line, to solve the problem of control of voltage and reactive power in multi-area power systems, are introduced and compared with each other and with the centralized method. The common point of these three methods is that they all use the Lagrange relaxation method to remove complex constraints. Examining the simulation results shows that the adjustment at the dummy boundary bus requires more iterations than the other two methods to achieve convergence, but the results of this method are closer to the results of the centralized solution method, its means, this method has lower sub-optimally. Also, unlike the centralized method that requires a lot of information exchange, the decomposition methods are less dependent on the exchange of information between areas, and among them, the method of adjustment at the dummy boundary bus requires the least exchange. https://tjee.tabrizu.ac.ir/article_18531_52438b79d6f4afa94e975c43258d5632.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Enhancing Power System Resilience Against Natural Disaster Using A Proactive Strategy Enhancing Power System Resilience Against Natural Disaster Using A Proactive Strategy 595 604 18080 10.22034/tjee.2024.58937.4749 FA Mohammadali Nazari Department of Electrical and Computer Engineering, University of Kurdistan, Sanandaj, Iran Navid Rezaei Department of Electrical and Computer Engineering, University of Kurdistan, Sanandaj, Iran 0000-0002-8570-8301 Hassan Bevrani Department of Electrical and Computer Engineering, University of Kurdistan, Sanandaj, Iran . Journal Article 2023 10 22 Enhancing power system resilience refers to the performance of the entire power system against severe natural events and even cyber attacks. As natural disasters increase year by in different countries, improving the resilience of power systems becomes more important than the past. The damages caused by these events amount to billions of dollars each year. Preparing the power system for such events, or in other words, making it resilient, can significantly reduce the damages. Various plans are proposed for pre-event resilience, during the event, and/or post-event. This article uses statistical methods and Markov probability to predict system failures and determines the distribution of generator outputs accordingly to minimize load shedding in the system. In fact, without planning and management distribution of outputs during the event, the operator will be forced to use corrective and emergency actions. In this article, a corrective method is compared with the proposed method, demonstrating the effectiveness of the proposed method in reducing load shedding. Enhancing power system resilience refers to the performance of the entire power system against severe natural events and even cyber attacks. As natural disasters increase year by in different countries, improving the resilience of power systems becomes more important than the past. The damages caused by these events amount to billions of dollars each year. Preparing the power system for such events, or in other words, making it resilient, can significantly reduce the damages. Various plans are proposed for pre-event resilience, during the event, and/or post-event. This article uses statistical methods and Markov probability to predict system failures and determines the distribution of generator outputs accordingly to minimize load shedding in the system. In fact, without planning and management distribution of outputs during the event, the operator will be forced to use corrective and emergency actions. In this article, a corrective method is compared with the proposed method, demonstrating the effectiveness of the proposed method in reducing load shedding. https://tjee.tabrizu.ac.ir/article_18080_9025b5dc07140259cd55eccb1a4c17f7.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Scalable and Anonymous Computation Offloading Solution in Blockchain Scalable and Anonymous Computation Offloading Solution in Blockchain 605 613 18412 10.22034/tjee.2024.59762.4785 FA Shokufeh Norouzi PhD Student, School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran. Yuoosef Ghobadi MSc Graduated, School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran. Zeinab Movahedi Associate Professor, Faculty of Computer Engineering, School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran. Journal Article 2023 12 25 Today, with the implementation of the new generation of communication networks, we are witnessing a huge evolution in the development of the Internet of Things (IoT) and the emergence of new programs in this context. The limitation in the computing power and energy of the devices connected to this platform creates a challenge and lack of support for these devices to run programs with high computation load and low delay. Computation offloading in the cloud and edge network has been introduced as a suitable approach to deal with these limitations. Using the capacity of devices with appropriate power in the vicinity of IoT devices as an offloading destination prevents the exchange of a huge amount of data in the network core. The use of these devices requires maintaining the privacy and security of the offloaded workload so that the sensitive and confidential information of IoT users is not compromised during the computation offloading process. For this purpose, blockchain is used. Blockchain technology has unique features such as transparency, immutability and decentralization, securing and automating applications, which makes it a suitable option for securing the transfer and storage of data generated in the IoT platform. The use of blockchain in computation offloading faces limitations such as managing a large number of requests due to the expensive design of consensus methods. In addition, by analyzing the transactions and traffic, the influential groups can obtain the identity of the owners of the offloaded workloads and their sensitive content and violate the privacy. In order to solve these challenges, this article takes a step forward by presenting a scalable and anonymous computation offloading method in blockchain. The proposed approach changes the blockchain architecture using Merkel chain as a Directed Acyclic Graph and optimizes the consensus method to solve the challenges of scalability. As well, the proposed appraoch uses the zero-knowledge proof to improve privacy and anonymity. Today, with the implementation of the new generation of communication networks, we are witnessing a huge evolution in the development of the Internet of Things (IoT) and the emergence of new programs in this context. The limitation in the computing power and energy of the devices connected to this platform creates a challenge and lack of support for these devices to run programs with high computation load and low delay. Computation offloading in the cloud and edge network has been introduced as a suitable approach to deal with these limitations. Using the capacity of devices with appropriate power in the vicinity of IoT devices as an offloading destination prevents the exchange of a huge amount of data in the network core. The use of these devices requires maintaining the privacy and security of the offloaded workload so that the sensitive and confidential information of IoT users is not compromised during the computation offloading process. For this purpose, blockchain is used. Blockchain technology has unique features such as transparency, immutability and decentralization, securing and automating applications, which makes it a suitable option for securing the transfer and storage of data generated in the IoT platform. The use of blockchain in computation offloading faces limitations such as managing a large number of requests due to the expensive design of consensus methods. In addition, by analyzing the transactions and traffic, the influential groups can obtain the identity of the owners of the offloaded workloads and their sensitive content and violate the privacy. In order to solve these challenges, this article takes a step forward by presenting a scalable and anonymous computation offloading method in blockchain. The proposed approach changes the blockchain architecture using Merkel chain as a Directed Acyclic Graph and optimizes the consensus method to solve the challenges of scalability. As well, the proposed appraoch uses the zero-knowledge proof to improve privacy and anonymity. https://tjee.tabrizu.ac.ir/article_18412_ba41dadb09fa0fe782cc922a239f8587.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Enhanced Fault Detection in MicroLEDs through Microphotoluminescence Microscope Construction Enhanced Fault Detection in MicroLEDs through Microphotoluminescence Microscope Construction 615 621 18679 10.22034/tjee.2024.61975.4858 FA Mohammad Hendijanifard School of Mechanical Engineering, Shiraz University, Shiraz, Iran Journal Article 2024 06 12 The microphotoluminescence microscope has been developed by integrating 405 nm excitation lasers into a conventional optical microscope system, enabling enhanced characterization of microLED devices. These lasers excite the photoluminescence bands of blue microLEDs, which emit at a wavelength of 450 nm. Defective or short-circuited microLED quantum wells fail to emit light under excitation and thus appear as dark spots in the captured images. This contrast facilitates the automatic identification and mapping of faulty microLEDs through advanced image processing algorithms. Early detection of defective microLEDs at the wafer processing stage within LED manufacturing facilities is crucial, as it allows manufacturers to promptly discard or reprocess faulty wafers, significantly reducing production costs and improving overall yield. Furthermore, the microphotoluminescence microscope provides a powerful tool for quality assurance by enabling detailed comparisons of microLED quality across different wafer batches. It also enhances the detection of substantial defects that can easily be overlooked by conventional microscopy techniques. Overall, the integration of this technology offers a cost-effective and efficient approach for in-line inspection and quality control in microLED production. The microphotoluminescence microscope has been developed by integrating 405 nm excitation lasers into a conventional optical microscope system, enabling enhanced characterization of microLED devices. These lasers excite the photoluminescence bands of blue microLEDs, which emit at a wavelength of 450 nm. Defective or short-circuited microLED quantum wells fail to emit light under excitation and thus appear as dark spots in the captured images. This contrast facilitates the automatic identification and mapping of faulty microLEDs through advanced image processing algorithms. Early detection of defective microLEDs at the wafer processing stage within LED manufacturing facilities is crucial, as it allows manufacturers to promptly discard or reprocess faulty wafers, significantly reducing production costs and improving overall yield. Furthermore, the microphotoluminescence microscope provides a powerful tool for quality assurance by enabling detailed comparisons of microLED quality across different wafer batches. It also enhances the detection of substantial defects that can easily be overlooked by conventional microscopy techniques. Overall, the integration of this technology offers a cost-effective and efficient approach for in-line inspection and quality control in microLED production. https://tjee.tabrizu.ac.ir/article_18679_20f1c9afde3ffea2d4c06dc42974be84.pdf

University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 55 3 2025 12 22 Local Binary Pattern Analysis of Foot Pressure Signals for Stroke Detection Local Binary Pattern Analysis of Foot Pressure Signals for Stroke Detection 623 631 18081 10.22034/tjee.2024.59207.4759 FA Arefeh Yagoubi M.Sc. Student, Faculty of Biomedical Engineering, Sahand University of Technology, Tabriz, Iran, Peyvand Ghaderyan Associate Professor, Faculty of Biomedical Engineering, Sahand University of Technology, Tabriz, Iran, Journal Article 2023 11 14 Stroke patients generally exhibit trouble walking and moving, which affects their quality of life. Hence, an accurate diagnosis of stroke is important for providing an effective treatment and rehabilitation strategy. However, the development of a cost-effective and non-invasive diagnostic tool is a big challenge for clinical applications. To address this challenge, in this study, a new ischemic stroke detection has been proposed based on structural features of foot plantar pressure signals and support vector machine classifier. A local uniform binary pattern extracted from the time-frequency representation of pressure signals has been used to capture the local structure over two-dimensional space and quantify the stability of this pattern. The proposed method has been evaluated using the pressure signals recorded during normal walking tasks from 36 healthy controls and 46 Ischemic stroke patients. The classification has also been performed for different plantar channels to offer regional analysis. The obtained results have achieved a high average accuracy rate of 99.66% for stroke detection. Furthermore, the robustness of the proposed method against different plantar regions as well as technical parameters of the local binary pattern approach has been demonstrated in an experimental comparative study. The performance has confirmed that the local binary pattern analysis discriminates effectively stroke patients and healthy controls when foot plantar pressure signals are used. Stroke patients generally exhibit trouble walking and moving, which affects their quality of life. Hence, an accurate diagnosis of stroke is important for providing an effective treatment and rehabilitation strategy. However, the development of a cost-effective and non-invasive diagnostic tool is a big challenge for clinical applications. To address this challenge, in this study, a new ischemic stroke detection has been proposed based on structural features of foot plantar pressure signals and support vector machine classifier. A local uniform binary pattern extracted from the time-frequency representation of pressure signals has been used to capture the local structure over two-dimensional space and quantify the stability of this pattern. The proposed method has been evaluated using the pressure signals recorded during normal walking tasks from 36 healthy controls and 46 Ischemic stroke patients. The classification has also been performed for different plantar channels to offer regional analysis. The obtained results have achieved a high average accuracy rate of 99.66% for stroke detection. Furthermore, the robustness of the proposed method against different plantar regions as well as technical parameters of the local binary pattern approach has been demonstrated in an experimental comparative study. The performance has confirmed that the local binary pattern analysis discriminates effectively stroke patients and healthy controls when foot plantar pressure signals are used. https://tjee.tabrizu.ac.ir/article_18081_58fa1f1788901f632c7bde12143dfe4d.pdf