Original Research Paper
Electrical Machines
R. Rouhani; S.E. Abdollahi; A. Gholamian
Abstract
Background and Objectives: The rotor of synchronous reluctance machines (SynRM) is conventionally designed and implemented in two types of axially-laminated anisotropic (ALA) and transversely-laminated anisotropic (TLA). Torque ripple and power factor have always been the design challenges of this machine; ...
Read More
Background and Objectives: The rotor of synchronous reluctance machines (SynRM) is conventionally designed and implemented in two types of axially-laminated anisotropic (ALA) and transversely-laminated anisotropic (TLA). Torque ripple and power factor have always been the design challenges of this machine; however, with proper design, their values can be as close as possible to the desired value. Each of these two structures has some advantages over the other, in terms of electromagnetic performance and ease of construction. For the first time, in this paper, a hybrid anisotropic rotor is presented with both radial and axial laminations, Based on the theory of anisotropic rotor structure for the fundamental harmonic and isotropic rotor structure for other harmonics, so that the designed motor meets the advantages of both structures as much as possible.Methods: To this end, the proposed design is implemented and investigated a Magnetic Equivalent Circuit(MEC) for the first slot harmonic on a machine with stator of 24-slots. To evaluate the proposed design, its electromagnetic performance is simulated using Finite Element Method.Results: The theory-based conceptual design method is applied to a rotor with new structure and simulation results including average torque, power factor and torque ripple of the machine are presented.Conclusion: Based on the obtained simulation results and comparing performance of the proposed design with other structures, it is shown that there will be a significant improvement in electromagnetic features including torque ripple, average torque and power factor and the proposed design has lower torque ripple than ALA rotor and higher average torque and power factor than TLA rotor.
Original Research Paper
Linear Induction Motors
P. Hamedani; S. Sadr
Abstract
Background and Objectives: Linear Induction Motors (LIMs) are favorite machines utilized in various industrial applications. But, due to the end effect phenomena, control of a LIM drive is more complicated than rotational machine drives. Therefore, selecting the proper control strategy for a LIM drive ...
Read More
Background and Objectives: Linear Induction Motors (LIMs) are favorite machines utilized in various industrial applications. But, due to the end effect phenomena, control of a LIM drive is more complicated than rotational machine drives. Therefore, selecting the proper control strategy for a LIM drive has been a significant challenge for the researchers.Methods: This paper concentrates on a new Model Predictive Control (MPC) of LIM drives which considers the end effect.Accordingly, the discrete-time model of the LIM with end effect is extracted, and the required flowchart used for the MPC of LIM drive has been presented in this paper.Results: To study the effectiveness of the suggested strategy, simulation results of a LIM drive with MPC are presented and compared to the traditional Indirect Field Oriented Control (IFOC) of LIM drive. Simulations have been carried out using Matlab. The end effect has been considered in the LIM model and control strategies.Conclusion: Simulation results validate that the suggested MPC of LIM drive yields excellent dynamic characteristics such as fast speed response with no overshoot. Moreover, in comparison to the traditional IFOC method, the suggested MPC strategy offers lower current ripple and lower electromagnetic force ripple, and therefore, it is suitable for industrial drive applications.
Original Research Paper
Information Hiding
V. Sabeti
Abstract
Background and Objectives: Steganalysis is the study of detecting messages hidden using steganography. Most steganalysis techniques, known as blind steganalysis, focus on extracting and classifying various statistical features from images. Consequently, researchers continually seek to improve the accuracy ...
Read More
Background and Objectives: Steganalysis is the study of detecting messages hidden using steganography. Most steganalysis techniques, known as blind steganalysis, focus on extracting and classifying various statistical features from images. Consequently, researchers continually seek to improve the accuracy of blind detection methods. The current study proposes a blind steganalysis technique based on overlapping blocks.Methods: The proposed method began by decomposing the image into identically sized overlapping blocks, then extracted a feature vector from each block. Subsequently, a tree-structured hierarchical clustering technique was used to partition blocks into multiple classes based on extracted features, and a classifier was trained for each class to determine whether a block is from a cover or stego image. The block decomposition process was repeated for each test image, and a classifier was selected based on the block class to make a decision for each block. Furthermore, the majority vote rule was utilized to determine whether the test image is a cover or stego image.Results: The proposed method was evaluated using the INRIA and BOSSbase datasets. Several parameters, including the number of block classes, feature extraction method, block size, and number and block overlapping level, affected the performance of the proposed method. The optimal block size was 64 × 64 by 32 steps, and the number of block classes was set to 16. WOW, S-UNIWARD, PQ, and nsF5 were the steganographic methods employed to evaluate the proposed method. Experimental results indicated that using overlapping instead of non-overlapping blocks increased the detection of data embedded in both the spatial and Joint Photographic Experts Group (JPEG) domains by an average of over 9%. In addition, the proposed method's accuracy in detecting the S-UNIWARD method was comparable to that of other deep learning-based steganalysis techniques.Conclusion: The concept of using overlapping blocks improves the efficiency of blind steganalysis by providing the benefit of additional and larger blocks. One of the main advantages of the proposed method is comparable detection accuracy and less computational complexity than recent deep learning-based steganalysis techniques.
Original Research Paper
Wind Turbine
M. Kamarzarrin; M.H. Refan; P. Amiri; A. Dameshghi
Abstract
Background and Objectives: Renewable energy, like wind turbines, is growing rapidly in the world today due to environmental pollution, so their maintenance plans are very important. Fault diagnosis and fault-tolerant approaches are typical methods to reduce the cost of energy production and downtime ...
Read More
Background and Objectives: Renewable energy, like wind turbines, is growing rapidly in the world today due to environmental pollution, so their maintenance plans are very important. Fault diagnosis and fault-tolerant approaches are typical methods to reduce the cost of energy production and downtime of Wind Turbines (WTs). Methods: In this paper, a new Hardware In the Loop (HIL) simulator based on Double Feed Induction Generator (DFIG) for fault diagnosis and fault-tolerant control is proposed. The system developed as a laboratory bed uses a generator with a power of about 90 kW, which is connected from two sides to a back-to-back power converter with a power of one-third of the generator power. The generator is connected to a motor as a propulsion and wind energy replacement with a power of about 110 kW, and this connection is established through a gearbox with a gear ratio of more than three. Results: The effectiveness of the proposed simulator is evaluated based on different fault representations back-to-back converter and generator.Conclusion: The experiment shows that the Condition Based Maintenance (CBM) is improved by the proposed simulator and the fault is modeled before serious damage occurs. This setup is effective for the development of wind turbine fault analysis software. As the testing on real WTs is very expensive, to improve and develop the research fields of condition monitoring and WT control, this low-cost setup is effective.
Original Research Paper
Electrical Machines
S. Nasr; B. Ganji; M. Moallem
Abstract
Background and Objectives: Due to exclusive advantages of the permanent magnet synchronous motors (PMSMs) such as large torque/power density, high efficiency and wide speed range in constant power region, special attention has been paid to these motors especially for electric vehicle (EV) application. ...
Read More
Background and Objectives: Due to exclusive advantages of the permanent magnet synchronous motors (PMSMs) such as large torque/power density, high efficiency and wide speed range in constant power region, special attention has been paid to these motors especially for electric vehicle (EV) application. A conventional type of PMSMs which is more suitable for EV application is the interior permanent magnet synchronous motors (IPMSM). The main objective of the present paper is design optimization of this type of PMSM to increase efficiency and reduce torque ripple which are important for EV application. Methods: Using different shape design optimization methods including rotor notch, flux barrier and skewed rotor, design optimization of the delta-shape IPMSM is done and an optimized design is suggested first. One of the most important factors affecting the performance of the IPMSM is the magnet arrangement in the rotor structure. Based on the the design of experiments (DOE) algorithm, optimal values of some design parameters related to magnet are then determined to improve more the motor performance of the suggested structure.Results: The simulation results based on finite element method (FEM) are provided for a typical high-power IPMSM to evaluate the effectiveness of the proposed technique. In comparison to the initial design, 7% increase of average torque, 50% reduction of torque ripple and 1.4% increase of efficiency are resulted for the optimized motor. Conclusion: Using the proposed hybrid design optimization procedure (shape design optimization with optimum design parameters), significant improvement of some characteristics related to the delta-shape IPMSM including efficiency, average torque and torque ripple is resulted and this conclusion is desirable for EV application.
Original Research Paper
Communications
B. Norsabbaghi; G. Baghersalimi; A. Pouralizadeh; O. Mohammadian
Abstract
Background and Objectives: High peak-to-average power ratio (PAPR) in Orthogonal Frequency Division Multiplexing (OFDM)-based Underwater Optical Wireless Communication (UOWC) systems is one of the most important reasons for out-of-band power and in-band distortion leading to the declination of system ...
Read More
Background and Objectives: High peak-to-average power ratio (PAPR) in Orthogonal Frequency Division Multiplexing (OFDM)-based Underwater Optical Wireless Communication (UOWC) systems is one of the most important reasons for out-of-band power and in-band distortion leading to the declination of system performance. Therefore, different approaches have been suggested and implemented for decreasing high PAPR of OFDM signals in UOWC systems that is the main aim of this paper.Methods: In this research, the performance of an OFDM-based UOWC system is investigated by employing Repetitive Clipping and Filtering (RCF) technique in clear open ocean water. The Monte Carlo Modeling of Light (MCML) approach with the Henyey Greenstein (HG) model of the scattering phase function is used to simulate the UOWC channel. Results: First, the CCDF performance of the suggested system with RCF method for different CR values is investigated. Also, the proposed system performance is examined in terms of bit error rate (BER) and error vector magnitude (EVM) at two different depths for link lengths of 1m and 5 m.Conclusion: The results showed that the system performance is limited by increasing the link length, the number of subcarriers, and depth. Also, it is shown that the RCF method significantly leads to reduction of the PAPR in the DCO-OFDM UWOC system and enhance BER performance up to 10 dB.
Original Research Paper
Deep Learning
M. Taherparvar; F. Ahmadi Abkenari; P. Bayat
Abstract
Background and Objectives: Embedding social networks has attracted researchers’ attention so far. The aim of network embedding is to learn a low-dimensional representation of each network vertex while maintaining the structure and characteristics of the network. Most of these existing network embedding ...
Read More
Background and Objectives: Embedding social networks has attracted researchers’ attention so far. The aim of network embedding is to learn a low-dimensional representation of each network vertex while maintaining the structure and characteristics of the network. Most of these existing network embedding methods focus on only preserving the structure of networks, but they mostly ignore the semantic and centrality-based information. Moreover, the vertices selection has been done blindly (greedy) in the existing methods.Methods: In this paper, a comprehensive algorithm entitled CSRW stands for centrality, and a semantic-based random walk is proposed for the network embedding process based on the main criteria of the centrality concept as well as the semantic impact of the textual information of each vertex and considering the impact of neighboring nodes. in CSRW, textual analysis based on the BTM topic modelling approach is investigated and the final display is performed using the Skip-Gram model in the network.Results: The conducted experiments have shown the robustness of the proposed method of this paper in comparison to other existing classical approaches such as DeepWalk, CARE, CONE, COANE, and DCB in terms of vertex classification, and link prediction. And in the criterion of link prediction in a Subgraph with 5000 members, an accuracy of 0.91 has been reached for the criterion of closeness centrality and is better than other methods.Conclusion: The CSRW algorithm is scalable and has achieved higher accuracy on larger datasets.
Original Research Paper
Antenna Design
R. Shirmohamadi; M. Bod; G. Dadashzadeh
Abstract
Background and Objectives: Multi-input multi-output (MIMO) antennas have been of interest in wireless communications in recent years. In these systems, many antennas are placed next to each other. The most important issue in the design of MIMO antennas is mutual coupling. Many methods have been proposed ...
Read More
Background and Objectives: Multi-input multi-output (MIMO) antennas have been of interest in wireless communications in recent years. In these systems, many antennas are placed next to each other. The most important issue in the design of MIMO antennas is mutual coupling. Many methods have been proposed to reduce the mutual coupling of MIMO antennas. Many of these methods require an additional substrate on top or bottom of the antenna. In the reduction of mutual couplings electromagnetic band-gap (EBG) structures are preferred because they are coplanar with the antenna and can be compactly designed. In this paper, to reduce mutual coupling in MIMO antennas, a novel compact EBG structure based on the genetic algorithm optimization is proposed.Methods: The method proposed in this paper to design an optimal EBG structure is to use a genetic algorithm (GA). In this method, an EBG unit cell is designed by a binary code, and then the 7×2 EBG structure of the unit cell is placed between two antenna elements with λ/2 distance. The optimization algorithm tries to find the best unit cell to reduce the mutual coupling between two elements. After 70 generations in the genetic algorithm, the GA determines a compact structure of EBG elements which reduces mutual coupling significantly.Results: Two-element patch antennas with and without the proposed EBG structure are fabricated and the mutual couplings between array elements are measured at 5.68GHz in both cases. It is shown that the proposed compact EBG structure reduced the isolation of the two antennas by 27 dB. This decrease in mutual coupling is much higher than in the previous papers. The proposed EBG has little effect on other antenna radiation parameters such as S11 and radiation patterns.Conclusion: In general, in this paper, a compact and coplanar EBG structure is proposed to significantly reduce the mutual coupling in MIMO antennas. The method presented in this paper can be used for other MIMO antenna configurations at other frequencies and the proposed method will create a completely optimal structure to reduce mutual coupling.
Original Research Paper
Cryptography
B. Sefid-Dashti; J. Salimi Sartakhti; H. Daghigh
Abstract
Background and Objectives: Cryptographic hash functions are the linchpins of mobile services, blockchains, and many other technologies. Designing cryptographic hash functions has been approached by research communities from the physics, mathematics, computer science, and electrical engineering fields. ...
Read More
Background and Objectives: Cryptographic hash functions are the linchpins of mobile services, blockchains, and many other technologies. Designing cryptographic hash functions has been approached by research communities from the physics, mathematics, computer science, and electrical engineering fields. The emergence of new hash functions, new hash constructions, and new requirements for application-specific hash functions, such as the ones of mobile services, have encouraged us to make a comparison of different hash functions and propose a new classification.Methods: Over 100 papers were surveyed and reviewed in detail. The research conducted in this paper has included four sections; article selection, detailed review of selected articles, data collection, and evaluation of results. Data were collected as new hash function properties, new hash function constructions, new hash function categories, and existing hash function attacks which are used to evaluate the results.Results: This paper surveys seven categories of hash functions including block cipher-based functions, algebraic-based functions, custom-designed functions, Memory-hard Functions (MHFs), Physical Unclonable Functions (PUFs), quantum hash functions and optical hash functions. To the best of our knowledge, the last four mentioned categories have not been sufficiently addressed in most existing surveys. Furthermore, this paper overviews hash-related adversaries and six hash construction variants. In addition, we employed the mentioned adversaries as evaluation criteria to illustrate how different categories of hash functions withstand the mentioned adversaries. Finally, the surveyed hash function categories were evaluated against mobile service requirements.Conclusion: In addition to new classification, our findings suggest using PUFs with polynomial-time error correction or possibly bitwise equivalents of algebraic structures that belongs to post-quantum cryptography as candidates to assist mobile service interaction requirements.
Original Research Paper
Electronics
B. Khosravi Rad; M. Khaje; A. Eslami Majd
Abstract
Background and Objectives: One of the common methods for measuring the contact resistance of graphene sheets is the transfer length or transmission line method (TLM). Apart from the contact resistance, TLM gives the resistance of the channel sheet and the effective transfer length of the measured samples. ...
Read More
Background and Objectives: One of the common methods for measuring the contact resistance of graphene sheets is the transfer length or transmission line method (TLM). Apart from the contact resistance, TLM gives the resistance of the channel sheet and the effective transfer length of the measured samples. Furthermore, the implementation of TLM is simple. To analyze this method, one can use circuit modeling (CM).Methods: An important parameter of TLM is the contact resistance between the metal electrode and the graphene channel. To compare this parameter with other measures, it is normalized by multiplying it by the channel width. In this research, for TLM analysis, all the components of the structure including electrodes, graphene channel, and metal-graphene contact are modeled in a circuit.Results: PSpice and MATLAB are integrated for TLM circuit modeling. The metal electrodes and the graphene channel are modeled based on the values of the resistances measured in the laboratory using the van der Pauw method and the resistances reported in the article in ohms per square. Moreover, the metal-graphene contact resistance is considered based on the values reported in the literature in ohms-micrometers.Conclusion: The modeling results show that, in addition to the effective transfer length, the effective transfer width can be defined on a contact, according to the dimensions of the structure. Therefore, the channel width is a vague characteristic of the TLM measurement, which plays a very important role in measuring contact resistance. Furthermore, the contact resistance and the resistance of the channel sheet are independent of each other and of the distance between the contacts. If defects in the graphene channel are randomly distributed along the channel between the contacts, they do not have a significant impact on the contact resistance, while they increase the resistance of the graphene sheet provided that they do not disrupt the channel. Indeed, for a 10% defect (or 90% coverage along the channel), the resistance of the sheet increases by 16%. In addition, by using this modeling, parameters such as the distribution of the contact current, the sources of errors, and their influence in determining the contact resistance and resistance of the channel sheet are investigated.
Original Research Paper
Natural Language Processing
Y. Saffari; J. Salimi Sartakhti
Abstract
Background and Objectives: Most of the recent dialogue policy learning methods are based on reinforcement learning (RL). However, the basic RL algorithms like deep Q-network, have drawbacks in environments with large state and action spaces such as dialogue systems. Most of the policy-based ...
Read More
Background and Objectives: Most of the recent dialogue policy learning methods are based on reinforcement learning (RL). However, the basic RL algorithms like deep Q-network, have drawbacks in environments with large state and action spaces such as dialogue systems. Most of the policy-based methods are slow, cause of the estimating of the action value using the computation of the sum of the discounted rewards for each action. In value-based RL methods, function approximation errors lead to overestimation in value estimation and finally suboptimal policies. There are works that try to resolve the mentioned problems using combining RL methods, but most of them were applied in the game environments, or they just focused on combining DQN variants. This paper for the first time presents a new method that combines actor-critic and double DQN named Double Actor-Critic (DAC), in the dialogue system, which significantly improves the stability, speed, and performance of dialogue policy learning. Methods: In the actor critic to overcome the slow learning of normal DQN, the critic unit approximates the value function and evaluates the quality of the policy used by the actor, which means that the actor can learn the policy faster. Moreover, to overcome the overestimation issue of DQN, double DQN is employed. Finally, to have a smoother update, a heuristic loss is introduced that chooses the minimum loss of actor-critic and double DQN. Results: Experiments in a movie ticket booking task show that the proposed method has more stable learning without drop after overestimation and can reach the threshold of learning in fewer episodes of learning. Conclusion: Unlike previous works that mostly focused on just proposing a combination of DQN variants, this study combines DQN variants with actor-critic to benefit from both policy-based and value-based RL methods and overcome two main issues of both of them, slow learning and overestimation. Experimental results show that the proposed method can make a more accurate conversation with a user as a dialogue policy learner.
Original Research Paper
Antenna Design
S. Komeylian; M. Tayarani; S.H. Sedighi
Abstract
Background and Objectives: Microstrip patch antennas are widely used due to their advantages of compact size and easy fabrication compared to other types. However, they have low-performance parameters. As a result, several techniques are used to improve performance parameters in newly designed microstrip ...
Read More
Background and Objectives: Microstrip patch antennas are widely used due to their advantages of compact size and easy fabrication compared to other types. However, they have low-performance parameters. As a result, several techniques are used to improve performance parameters in newly designed microstrip antennas. In this study, a novel miniaturized microstrip antenna with circular polarization (CP) is proposed for GNSS applications.Methods: In the design process, the semi-fractal structure is used to reduce the antenna size. Circular polarization is generated using a three-feed configuration with 120◦ phase shift. The CP value is increased by use of perturbing slots and also removing the corners. The novel design of the feeding network and also considering the ground size same as the patch layer, keep the antenna size small. The co-axial probe is used in the feeding network and it is printed on Taconic RF-43 substrate with a low loss tangent of 0.0033. Numerical simulation is applied via CST commercial software to evaluate the antenna performance. The simulations are repeated in two other software, HFSS and FEKO, to validate the study. Results: The proposed antenna has a compact size of 17.56 cm2. The single-layer structure of the designed antenna leads to easy fabrication feature. The proposed antenna has a bandwidth of 55 MHz (1.558-1.614 GHz). It can operate at GPS L1 (1575 MHz), GLONASS G1 (1602 MHz), Galileo E1 (1589 MHz), and E2 (1561 MHz) bands. Results show a high front-to-back ratio (FBR) of 40 dB, RHCP gain of 3.45 dB, and pure CP with axial ratio (AR) beamwidth of 108⸰. Furthermore, the phase center variation (PCV) is less than 0.16 mm.Conclusion: Key features of the proposed antenna are its novel fractal structure that leads to compact size, high front-to-back ratio, wide RHCP beamwidth with desirable bandwidth, and axial ratio beamwidth.
Original Research Paper
Arduino Uno
M. D. Enriquez; A. P. N. Abella
Abstract
Background and Objectives: Salt production is an ancient industry that still used primitive or traditional systems of evaporation. As technology continues to prosper in all aspects of life; the use of technology-based products is still a challenge in salt production. With the tedious activities and processes ...
Read More
Background and Objectives: Salt production is an ancient industry that still used primitive or traditional systems of evaporation. As technology continues to prosper in all aspects of life; the use of technology-based products is still a challenge in salt production. With the tedious activities and processes in salt farming; salt producers and salt farmers continue to look for alternatives to lessen the hard works. Salt farm activities initially started with the intrusion of saline water into the salt beds, but monitoring of the saline water is needed to ensure that only saline water can enter the salt farms to ensure the quantity and quality of salts.Methods: This study aims to present a GSM-based water salinity monitoring system to lessen the frequent and manual monitoring of water salinity. The system is equipped with a solar panel, solar charger control, 12V battery, 12V relay, Arduino Uno, and GSM Module. Results: The overall rating of 3.32 reflects that the developed system met the design functions; the materials are appropriate and the specifications meet the desired purpose; the system is efficient and consistent with its desired objectives of lessening the manual activities involved in the monitoring of water salinity. As the pH and conductivity sensors read the salinity value, it send signals to the Arduino Uno; when the salinity level reads 34,000-35,000ppm a signal trigger the GSM Module to send a message to the gate valve. The performance efficiency of the system implied that the reaction of the Arduino Uno in triggering the GSM Module is in real-time as the salinity readings are received.Conclusion: The real-time reaction of the Arduino Uno to send signals to the GSM Module proved the advantages of using the system and the automatic salinity readings can lessen the frequent and laborious activity in water salinity monitoring.
Original Research Paper
Quantum Computing
E. Nikahd; M. Houshmand; M. Houshmand
Abstract
Background and Objectives: One of the quantum computing models without a direct classical counterpart is one-way quantum computing (1WQC). The computations are represented by measurement patterns in this model. One of the main downsides of the 1WQC model is the much larger number of qubits in a measurement ...
Read More
Background and Objectives: One of the quantum computing models without a direct classical counterpart is one-way quantum computing (1WQC). The computations are represented by measurement patterns in this model. One of the main downsides of the 1WQC model is the much larger number of qubits in a measurement pattern, compared to its equivalent in the circuit model. Therefore, proposing a method for optimally using the physical qubits to implement a measurement pattern is of interest,Methods: In a measurement pattern, despite a large number of qubits, the measured qubit is not needed after each measurement and can be used as another logical qubit. In this study, by using this feature and presenting an integer linear programming (ILP) model to change the ordering of a standard measurement pattern actions, the number of physical qubits required to implement that measurement pattern is minimized. Results: In the proposed method, compared to the scheduling based on the standard pattern, the number of required physical qubits on benchmark circuits is reduced by 56.7% on average. Although the proposed method produces the optimal solution, one of the most important limitations of that and ILP-based methods, in general, is their high execution time and memory requirements, which grow exponentially with the increase of the problem size. Conclusions: In this study, an ILP model is proposed to minimize the number of physical qubits used to realize a measurement pattern by efficiently scheduling the operations and reusing the physical qubits. Due to its exponential complexity, the proposed method cannot be used for large measurement patterns whose solution can be conspired as future works.
Original Research Paper
Artificial Intelligence
S. Kalantary; J. Akbari Torkestani; A. Shahidinejad
Abstract
Background and Objectives: With the great growth of applications sensitive to latency, and efforts to reduce latency and cost and to improve the quality of service on the Internet of Things ecosystem, cloud computing and communication between things and the cloud are costly and inefficient; Therefore, ...
Read More
Background and Objectives: With the great growth of applications sensitive to latency, and efforts to reduce latency and cost and to improve the quality of service on the Internet of Things ecosystem, cloud computing and communication between things and the cloud are costly and inefficient; Therefore, fog computing has been proposed to prevent sending large volumes of data generated by things to cloud centers and, if possible, to process some requests. Today's advances in 5G networks and the Internet of Things show the benefits of fog computing more than ever before, so that services can be delivered with very little delay as resources and features of fog nodes approach the end user.Methods: Since the cloud-fog paradigm is a layered architecture, to reduce the overall delay, the fog layer is divided into two sub-layers in this paper, including super nodes and ordinary nodes in order to use the coverage of super peer networks to use the connections between fog nodes in addition to taking advantage of the features of that network and improving the performance of large-scale systems. It causes fog nodes to interact with each other in processing requests and fewer data will be sent to the cloud, resulting in a reduction in overall latency. To reduce the cost of bandwidth used among fog nodes, we have organized a sub-layer of super nodes in the form of a Perfect Difference Graph (PDG). The new platform proposed for aggregation of fog computing and Internet of Things (FOT) is called the P2P-based Fog supported Platform (PFP).Results: We evaluate the utility of our proposed method by applying ifogsim simulator and the results achieved are as follows: (1) power consumption parameter in our proposed method 24% and 38% have improved compared to the structure three-layer fog computing architecture and without fog layer respectively; (2) network usage parameter in our proposed method 26% and 32% have improved compared to the structure three-layer fog computing architecture and without fog layer respectively; (3) average response time parameter in our proposed method 17% and 58% have improved compared to the structure three-layer fog computing architecture and without fog layer respectively; and (4) delay parameter in our proposed method 1% and 0.4% have improved compared to the structure three-layer fog computing architecture and without fog layer respectively.Conclusion: Numerical results obtained from the simulation show that the delay and cost parameters are significantly improved compared to the structure without fog layer and three-layer fog computing architecture. Also, the results show that increasing number of things has the same effect in all cases.
Original Research Paper
Computer Vision
S. H. Safavi; M. Sadeghi; M. Ebadpour
Abstract
Background and Objectives: Persian Road Surface Markings (PRSMs) recognition is a prerequisite for future intelligent vehicles in Iran. First, the existence of Persian texts on the Road Surface Markings (RSMs) makes it challenging. Second, the RSM could appear on the road with different qualities, such ...
Read More
Background and Objectives: Persian Road Surface Markings (PRSMs) recognition is a prerequisite for future intelligent vehicles in Iran. First, the existence of Persian texts on the Road Surface Markings (RSMs) makes it challenging. Second, the RSM could appear on the road with different qualities, such as poor, fair, and excellent quality. Since the type of poor-quality RSM is variable from one province to another (i.e., varying road structure and scene complexity), it is a very essential and challenging task to recognize unforeseen poor-quality RSMs. Third, almost all existed datasets have imbalanced classes that affect the accuracy of the recognition problem. Methods: To address the first challenge, the proposed Persian Road Surface Recognizer (PRSR) approach hierarchically separates the texts and symbols before recognition. To this end, the Symbol Text Separator Network (STS-Net) is proposed. Consequently, the proposed Text Recognizer Network (TR-Net) and Symbol Recognizer Network (SR-Net) respectively recognize the text and symbol. To investigate the second challenge, we introduce two different scenario. Scenario A: Conventional random splitting training and testing data. Scenario B: Since the PRSM dataset include few images of different distance from each scene of RSM, it is highly probable that at least one of these images appear in the training set, making the recognition process easy. Since in any province of Iran, we may see a new type of poor quality RSM, which is unforeseen before (in training set), we design a realistic and challengeable scenario B in which the network is trained using excellent and fair quality RSMs and tested on poor quality ones. Besides, we propose to use the data augmentation technique to overcome the class imbalanced data challenge.Results: The proposed approach achieves reliable performance (precision of 73.37% for scenario B) on the PRSM dataset . It significantly improves the recognition accuracy up to 15% in different scenarios.Conclusion: Since the PRSMs include both Persian texts (with different styles) and symbols, prior to recognition process, separating the text and symbol by a proposed STS-Net could increase the recognition rate. Deploying new powerful networks and investigating new techniques to deal with class imbalanced data in the recognition problem of the PRSM dataset as well as data augmentation would be an interesting future work.
Original Research Paper
Digital Signal Processing
A. Maroosi; H. Khaleghi Bizaki
Abstract
Background and Objectives: Subsampling methods allow sampling signals at rates much lower than Nyquist rate by using low-cost and low-power analog-to-digital converters (ADC). These methods are important for systems such as sensor networks that the cost and power consumption of sensors are the core issue ...
Read More
Background and Objectives: Subsampling methods allow sampling signals at rates much lower than Nyquist rate by using low-cost and low-power analog-to-digital converters (ADC). These methods are important for systems such as sensor networks that the cost and power consumption of sensors are the core issue in them. The Chinese remainder theorem (CRT) reconstructs a large integer (input frequency) from its multiple remainders (aliased or under-sampled frequencies), which are produced from under-sampling or integer division by several smaller positive integers. Sampling frequencies can be reduced by approaches based on CRT.Methods: The largest dynamic range of a generalized Chinese remainder theorem for two integers (input frequencies) has already been introduced in previous works. This is equivalent to determine the largest possible range of the frequencies for a sinusoidal waveform with two frequencies which the frequencies of the signal can be reconstructed uniquely by very low sampling frequencies. In this study, the largest dynamic range of CRT for any number of integers (any number of frequencies in a sinusoidal waveform) is proposed. It is also shown that the previous largest dynamic range for two frequencies in a waveform is a special case of our proposed procedure. Results: A procedure for multiple frequencies detection from reminders (under-sampled frequencies) is proposed and maximum tolerable noises of under-sampled frequencies for unique detection is obtained. The numerical examples show that the proposed approach, in some cases, can gain 11.5 times higher dynamic range than the conventional methods for a multi-sensor under-sampling system.Conclusion: Other studies introduced the largest dynamic range for the unique reconstruction of two frequencies by CRT. In this study, the largest dynamic ranges for any number of frequencies are investigated. Moreover, tolerable noise is also considered.
Original Research Paper
Electronic Circuits
M. A. Latifzadeh; P. Amiri; H. Allahyari; H. Faezi
Abstract
Background and Objectives: Many applications use boost converters as front-end circuits, including power factor correction (PFC), solar power generation, fuel cell power conversion, battery chargers, and uninterruptible power supply. In addition, boost converters have a simple structure with low component ...
Read More
Background and Objectives: Many applications use boost converters as front-end circuits, including power factor correction (PFC), solar power generation, fuel cell power conversion, battery chargers, and uninterruptible power supply. In addition, boost converters have a simple structure with low component counts, which makes them a convenient choice.Methods: This article proposes a coupled-inductor active auxiliary circuit to create a new low-stress boost converter with soft-switching. The proposed auxiliary circuit supplies the main switch and diode with soft-switching ZVC turn-on and ZCS turn-off states. The main switch and diode are not deal with any extra stress of voltage or current. Furthermore, the soft switching condition is also provided for auxiliary circuit components.Results: The proposed auxiliary circuit also has a simple structure, low circulating current losses, low cost, and simplicity in control. The operation state and performance of the proposed soft-switching boost converter are examined, and the design procedure is presented. Finally, a 200W prototype is implemented and tested to validate the theoretical results. The offered experimental data verified the theoretical analysis.Conclusion: This paper provides a new low-stress soft-switching boost converter using a simple coupled-inductor in the auxiliary circuit. Moreover, the auxiliary part consists of two diodes, one switch, one resonance capacitor, and a coupled inductor. The suggested auxiliary circuit provides soft switching condition for the main switch, which provides ZVS in the turn-on transient and ZCS in the turn-off transient, while in this situation, the soft-switching condition is provided for the auxiliary switch, which turns on under ZCS and also turns off with practically ZVS conditions. The auxiliary circuit does not impose additional voltage or current stress on the main switch. A 200 W prototype is implemented to validate the performance of this snubber cell. The experimental data reported here support the theoretical analysis. The best point of efficiency is 95.9% which is occurred at maximum load, and is 6.3% greater than the traditional counterparts.
Original Research Paper
Graph Clustering
M. Ghadirian; N. Bigdeli
Abstract
Background and Objectives: Community detection is a critical problem in investigating complex networks. Community detection based on modularity/general modularity density are the popular methods with the advantage of using complex network features and the disadvantage of being NP-hard ...
Read More
Background and Objectives: Community detection is a critical problem in investigating complex networks. Community detection based on modularity/general modularity density are the popular methods with the advantage of using complex network features and the disadvantage of being NP-hard problem for clustering. Moreover, Non-negative matrix factorization (NMF)-based community detection methods are a family of community detection tools that utilize network topology; but most of them cannot thoroughly exploit network features. In this paper, a hybrid NMF-based community detection infrastructure is developed, including modularity/ general modularity density as more comprehensive indices of networks. The proposed infrastructure enables to solve the challenges of combining the NMF method with modularity/general modularity density criteria and improves the community detection methods for complex networks.Methods: First, new representations, similar to the model of symmetric NMF, are derived for the model of community detection based on modularity/general modularity density. Next, these indices are innovatively augmented to the proposed hybrid NMF-based model as two novel models called ‘general modularity density NMF (GMDNMF) and mixed modularity NMF (MMNMF)’. In order to solve these two NP-hard problems, two iterative optimization algorithms are developed.Results: it is proved that the modularity/general modularity density-based community detection can be consistently represented in the form of SNMF-based community detection. The performances of the proposed models are verified on various artificial and real-world networks of different sizes. It is shown that MMNMF and GMDNMF models outperform other community detection methods. Moreover, the GMDNMF model has better performance with higher computational complexity compared to the MMNMF model.Conclusion: The results show that the proposed MMNMF model improves the performance of community detection based on NMF by employing the modularity index as a network feature for the NMF model, and the proposed GMDNMF model enhances NMF-based community detection by using the general modularity density index.
Original Research Paper
Lattice-based Cryptography
A. R. Payandeh; G. R. Moghissi
Abstract
Background and Objectives: Since exact manner of BKZ algorithm for higher block sizes cannot be studied by practical running, therefore simulation of BKZ is used to predict the total cost of BKZ and quality of output basis. This paper revises some main components of BKZ-simulation for better predictions.Methods: ...
Read More
Background and Objectives: Since exact manner of BKZ algorithm for higher block sizes cannot be studied by practical running, therefore simulation of BKZ is used to predict the total cost of BKZ and quality of output basis. This paper revises some main components of BKZ-simulation for better predictions.Methods: At first, by definition of full-enumeration success probability, the optimal enumeration radius is formally defined. Next, this paper defines three more pruning types, besides the well-known pruning by bounding function in GNR-enumerations, and consequently uses these four pruning types collectively in revision of success probability estimation. Also, by using these four pruning types and the process of updating-radius, this paper revises the estimation of enumeration cost. Finally, this paper introduces a simple technique to generate partially better bounding functions. Results: For block sizes of 50≤β≤240, better domains of radius parameters in GNR enumeration are formally introduced. Also, our revised estimation of success probability (for GNR bounding function) in our test results shows non-negligible gap from former estimations in some main former studies. Moreover, our results show that the cost results by our proposed estimator of GNR-enumeration cost are closer to the cost results determined in experimental running of enumeration, than the cost results by Chen-Nguyen estimator.Conclusion: This paper revises the estimators of cost and success probability for GNR-Enumeration, and justifies the value of these revised estimators by sufficient test results (in actual running and simulation of BKZ). Also our novel definition of optimal enumeration radius can be used effectively in actual running and simulation of BKZ.
', './data/jecei/coversheet/cover_en.jpg'))
