Amirkabir International Journal of Electrical & Electronics Engineering
Volume:55 Issue: 2, Summer-Autumn 2023

A novel metamaterial absorber sensor has been proposed for refractive index measurement in the range of [1-2] for the THz frequency band. This structure is based on using a plasmonic coaxial resonator which is excited by an InSb cylinder. Surface Plasmon Polaritons (SPPs) are excited on the surface of the InSb cylinder due to an inward plane wave and propagate downward toward the cavity and thru it. Based on the radius and height of the InSb cylinder, the “high-absorption” and “high-quality factor” sensing performance is introduced and analyzed. It is shown that nearly 98% absorption can be achieved for all the range of refractive index [1-2] at f = 1.8622 THz and in the case of “high-quality factor”, absorption reaches nearly 100% for the refractive index range of [1.5-2]. Also, by changing the radius and height of the cavity, absorption can be changed. Furthermore, sensitivity (S), quality factor (Q-factor), and figure of merit (FoM) in the range of 166-672 GHz per refractive index unit (GHz/RIU), 69.1-118.7 and 10.2- 29.7 is achievable, respectively. A wide range of refractive index measurements besides superior sensing performance made this structure a good candidate for sensing applications such as medical and biological or environmental applications.

This study investigates the effectiveness of mantle cloaking in isolating two densely packed patch antenna arrays with close operating frequencies. The cloak used is an elliptical metasurface consisting of vertical strips on a thin dielectric layer. This metasurface cloak reduces strong mutual coupling between adjacent elements of co-planar arrays by exhibiting capacitive reactance at the desired operating frequency and eliminating the inductive reactance caused by induced currents from adjacent patches. As a result, the elements of the two arrays become invisible to each other.To enable beam steering, the size of the patches is reduced by 34% through the addition of two slots on the resonant edges. The performance of the arrays is evaluated based on impedance matching, isolation, gain, radiation patterns, and efficiency. The results indicate that the addition of the cloak increased array efficiency by 35% compared to the uncloaked case. Additionally, the isolation between elements improved by over 15 dB at the operating frequency. The radiation patterns in the cloaked case closely resembled those of isolated arrays, with a similarity of 98%. However, in the cloaked case, there was a slight decrease in antenna gain by 0.7 dB and 0.5 dB for Array I and Array II, respectively. Furthermore, the sidelobe levels increased by 0.7 dB compared to isolated arrays. These findings confirm that the designed metasurface cloak effectively replicated the radiation characteristics of closely spaced arrays, resembling those of isolated arrays.

Here, it is investigated the results of implementation of interferometric optical fiber acoustic sensor based on fiber Bragg grating (FBG). It is investigated the importance of different types of interferometers configurations as Michelson or Mach-Zehnder interferometers on the signal to noise ratio. It is also considered the role of polymer coating on the increasing of signal to noise ratio. The results show, the Michelson interferometer setup using polymer packaging causes increasing signal to noise ratio. This latter configuration is used in a field setup in shallow water for acoustic signal detection in range of 0.5-5 kHz. The goal of this paper is extracting acoustical signal using optical signal via optical sensors and demodulation methods.Here, it is investigated the results of implementation of interferometric optical fiber acoustic sensor based on fiber Bragg grating (FBG). It is investigated the importance of different types of interferometers configurations as Michelson or Mach-Zehnder interferometers on the signal to noise ratio. It is also considered the role of polymer coating on the increasing of signal to noise ratio. The results show, the Michelson interferometer setup using polymer packaging causes increasing signal to noise ratio. This latter configuration is used in a field setup in shallow water for acoustic signal detection in range of 0.5-5 kHz. The goal of this paper is extracting acoustical signal using optical signal via optical sensors and demodulation methods.

The purpose of this article is to study the penetration of exogenous electric fields into the womb. It is postulated that the epithelial layer around the womb can act to prevent the penetration of such fields into the uterus, thereby effectively protecting the embryo from hazardous electric fields that have been shown to alter embryonic development. The very thin, low-conductivity epithelial layers are usually ignored in conventional 3D human body models used for dosimetry; i.e. to model electric field penetration in the body. However, these μm-thick layers can significantly influence the field distribution in the body due to their current-blocking or barrier function. In order to evaluate the effect of these layers at low frequencies, the epithelial layer was manually added to the uterine tissue in a 3D human body model. Then, the field distributions across the uterus were compared with and without the epithelial layer. This preliminary study showed that considering this layer at low frequencies can cause a 60% reduction in the electric field strength within the uterus. It is anticipated that if more exact estimations of uterine epithelium resistivity become available, the model could predict yet greater reductions and higher shielding can be assumed to occur in reality.

Backpropagation is the foremost prevalent and common algorithm for training conventional neural networks with deep construction. Here we propose DS4NN, temporal backpropagation for deep spiking neural networks with one spike per neuron. We consider a convolutional spiking neural network consisting of simple non-leaky integrate-and-fire (IF) neurons, and a form of coding named time-to-first-spike temporal coding in which, neurons are allowed to fire at most once in a specific time interval, which corresponds to simulation duration here. These features together improve the cost and the speed of network computation. We use a surrogate gradient at firing times to solve the non-differentiability of spike times with respect to the membrane potential of spiking neurons, and to prevent the emergence of dead neurons in deep layers, we propose a relative encoding scheme for determining desired firing times. Evaluations on two classification tasks of MNIST and Fashion-MNIST datasets confirm the capability of DS4NN on the deep structure of SNNs. It achieves the accuracy of 99.3% (99.8%) and 91.6% (95.3%) on testing samples (training samples) of respectively MNIST and Fashion-MNIST datasets with the mean required number of 1126 and 1863 spikes in the whole network. This shows that the proposed approach can make fast decisions with low-cost computation and high accuracy.

The Haplotype Assembly is the computational process in which two distinct nucleotide sequences of chromosomes are reconstructed using the sequencing reads of an individual. The ability to identify haplotypes provides many benefits for future genomic-based studies to be conducted in many areas, such as drug design, population study, and disease diagnosis. Even though several approaches have been put out to achieve highly accurate haplotypes, the problem of quick and precise haplotype assembly remains a challenging task. Due to the enormous bulk of the high-throughput sequencing data, algorithm speed plays a crucial role in the possibility of haplotype assembly in the human genome dimension. This study introduces a heuristic technique that enables rapid haplotype reconstruction while maintaining respectable accuracy. Our approach is divided into two parts. In the first, a partial haplotype is created and enlarged over a number of iterations. We have employed a novel metric to assess the reconstructed haplotype's quality in each iteration to arrive at the optimal answer. The second stage of the algorithm involves refining the reconstructed haplotypes to increase their accuracy. The outcome reveals that the suggested approach is capable of reconstructing the haplotypes with an acceptable level of accuracy. In terms of speed, the performance of the algorithm surpasses the competing approaches, especially in the case of high-coverage sequencing data.

Nowadays, non-linear loads are being used in distribution systems increasingly. Despite the good features such as low initial construction cost, high efficiency, and controllability, these loads cause harmonic distortions. In previous studies, passive harmonic filters have been proposed to decrease the produced harmonics, and to do so, various techniques have been suggested. However, the probability of daily load change, possible arrangements of distribution grid taking into consideration the filter design requirements and the impact of temperature change in harmonic filter parameters have been neglected in these studies. Therefore, in the current paper, a comprehensive model based on the probabilistic rearrangement of the distribution grid has been presented for the probabilistic planning of passive harmonic filters. In the proposed method, a two-level probabilistic optimization problem has been introduced with the objective of reducing harmonic distortions, voltage profile improvement, and loss, and investment cost reduction. As a result, the optimum placement of filters, the most optimal number and type of filters, and filter design parameters have been determined. The proposed procedure has been applied on the modified 33-bus IEEE network. The simulation results indicate that neglecting grid rearrangement may lead to a violation of power quality limits during some hours of the day. On the other hand, the combination of various network topologies in planning studies, ensures that the total harmonic distortion (THD) level is maintained within the standard range, guaranteeing loss, line density, and filter investment cost reduction.

The most important challenge in microgrids is the coordination of distributed energy resources (DERs), due to the existence of several DERs with fugacious characteristics. In this paper, a robust frame associated with a quantum version of the Teaching-Learning-Based Optimization (quantum TLBO) algorithm is proposed for the first time to the microgrid optimal energy management problem. Uncertainties in the load and in the output power of renewable energy sources are modeled using robust optimization (RO). The operation cost of the microgrid is considered as an objective function. The problem is formulated as a bi-level minimum-maximum optimization problem and is solved in two levels iteratively. First, by maximizing the operation cost of the microgrid, the worst case for the uncertain parameters is determined using Particle Swarm Optimization (PSO). Then, according to the results obtained in the first level, by minimizing the operation cost of the microgrid, the final optimal solution is obtained using the Quantum TLBO (QTLBO). This approach is applied to a grid-connected microgrid consisting of renewable energy sources, microturbine, fuel cell, and battery system. The obtained simulation results demonstrate that the QTLBO is significantly superior to the TLBO, Differential Evolution, and Real-Coded Genetic Algorithm in terms of both achieving the final optimal solution and convergence speed.

In this paper, with the use of adaptive-network-based fuzzy inference systems (ANFIS), closed-form expression for lightning-induced voltage of single-conductor overhead lines terminated with lightning arresters (overvoltage) is presented. The overhead line is stroked directly by lightning stroke. The lightning arresters are also grounded via two kinds of grounding systems namely vertical electrode and horizontal grid. Prior to creating the expression, at first a number of input-output pairs (inputs are resistivity of soil, overhead line height and electrode length while the output is the overvoltage across the arrester) are computed based on the exact models reported in the published literatures for the training process. Once the ANFIS algorithm is converged, the created simple expression can be easily used for efficient computation of overvoltage in soils with constant electrical parameters under arbitrarily-valued inputs which are different from samples selected in the training process. This simple expression can be easily used in dispersive soils and horizontally two-layered soils as well. To this end, the created ANFIS-based expression is integrated with equivalent resistivity approximations which leads to inclusion of the two effects separately and simultaneously in such complex soils. Evidently, this expression can be approximately used for three-conductor overhead lines which is of importance in practical point of view.

In this paper, the new structure N×M (N-Ternary inputs and M-Binary outputs) Ternary to Binary Converter based on Carbone Nanao Tube Field Effect Transistor is presented. The Carbone Nanao Tube Field Effect Transistor (CNTFET) has especial properties as controlled threshold voltage. The aforementioned advantages related to the multi-level (more specifically Ternary) circuits and systems based on CNTFET technology have encouraged researchers to put more effort on their design and realization in recent years. The Encoder (one input- five outputs), 3×1 multiplexer (one input – one selector-three outputs) and especial Adder blocks (Full Adder and Half Adder) are base blocks that are implemented by transistor level using especial properties of CNTFET transistor. In general, to implement a N-input ternary-to-binary converter, the number of inputs can be divided into two small converters, and also a ternary-to-binary converter can be designed for each input. In this paper, 2×4, 3×5, 4×7 and 5×8 Ternary to Binary converters are designed and simulated by Hospice and 32 nano meter technology. The result of simulation is shown that 5×8 Ternary to Binary converter has 1.89 µW DC-Power and 52 ps propagation delay. The proposed 5×8 TTBC converter is implemented by 365 CNTFET transistors and divided two ternary to binary converters.

The solar power tower (central receiver power plant) as one type of concentrated solar thermal power systems can be used to generate the electricity in a way similar to the thermal power plants and so, numerous large-scale central receiver power plants have been constructed and connected to the bulk power system to transfer their generated power to the power network. The variation in the solar radiation leads the generated power of these power plants changes, too. Thus, the integration of these large-scale solar power towers to the power system results in the some challenges that must be addressed. To study the effect of solar power towers on the power system, new techniques must be developed to consider the uncertainty nature of these plants. For this purpose, in this paper, to investigate the impact of central receiver power plants on the operation studies of the power system, the well-being approach is proposed. To consider the solar power towers in the operation studies of the power system, a multi-state model is developed for these plants that both variation in the generated power and failure of composed components are taken into account. To evaluate the effectiveness of the proposed technique, the well-being models of two reliability test system including RBTS and IEEE-RTS are determined and the effect of central receiver power plant on the operation indices such as health state probability, risk, spinning reserve, peak load carrying capability and increase in peak load carrying capability is investigated.

A structure for refractive index sensing application in THz band is proposed and analyzed in this paper. This structure is comprised of a golden plasmonic metamaterial absorber in which water is used as a dielectric and a thin topas layer-which does not have a significant effect on the performance of the sensor- is used for the separation of analyte and water. This structure has an absorption of 99.2% at resonance frequency 2.8725 THz. Lateral absorption frequency shift occurs due to variation in the refractive index (RI) of the analyte. This structure can be used for refractive index measurement in the range of 1-1.4 with full-width half maximum (FWHM), sensitivity (S), the figure of merit (FoM), and quality factor (Q-factor) in the ranges of 0.01647 THz, 427-644 GHz per refractive index unit (RIU), 6.3-26.5 and 26.23-175.5, respectively. It is worth mentioning that for a limited refractive index range 1.1 to 1.15, the values of FWHM, Q-factor, and FoM enhance to 0.0053327 THz, 516 and 90, respectively. The simplicity, compactness, ease of fabrication Due to the use of water as a dielectric along with appropriate refractive index sensitivity and FoM help this structure to use in biological , medical and environment sensing applications.