Iranian Journal of Electrical and Electronic Engineering
Volume:19 Issue: 3, Sep 2023

Speckle noise is an inherent artifact appearing in medical images that significantly lowers the quality and accuracy of diagnosis and treatment. Therefore, speckle reduction is considered as an essential step before processing and analyzing the ultrasound images. In this paper, we propose an ultrasound speckle reduction method based on speckle noise model estimation using a deep learning architecture called “speckle noise-based inception convolutional denoising neural network" (SNICDNN). Regarding the complicated nature of speckle noise, an inception module is added to the first layer to boost the power of feature extraction. Reconstruction of the despeckled image is performed by introducing a mathematical method based on solving a quadratic equation and applying an image-based inception convolutional denoising autoencoder (IICDAE). The results of various quantitative and qualitative evaluations on real ultrasound images demonstrate that SNICDNN outperforms the state-of-the-art methods for ultrasound despeckling. SNICDNN achieves 0.4579 dB and 0.0100 additional gains on average for PSNR and SSIM, respectively, compared to other methods. Denoising ultrasound based on its noise model estimation is not only a novel approach in comparison to traditional denoising autoencoder models but also due to the fact that it uses mathematical solutions to recover denoised images, SNICDNN shows a greater power in ultrasound despeckling.

The coronavirus disease or COVID-19, as a global disease, is an unprecedented health care crisis due to increasing mortality and its high rate of infection. Patients usually show significant complications in the respiratory system. This disease is caused by SARS-CoV-2. Decreasing the time of diagnosis is essential for reducing deaths and low spreading of the virus. Also, using the optimal tool in the pediatric setting and Intensive care unit (ICU) is required. Therefore, using lung ultrasound is recommended. It does not have any radiation and it has a lower cost. However, it makes noisy and low-quality data. In this paper, we propose a novel approach called Uniform Local Binary Pattern on Five intersecting Planes and convolutional neural Network (ULBPFP-Net) that overcomes the said limitation. We extract worthwhile features from five planes for feeding a network. Our experiments confirm the success of the ULBPFP-Net in COVID-19 diagnosis compared to the previous approaches.

This paper presents a low dropout voltage regulator, with the specifications suitable for hearing aid devices. The proposed LDO occupies very less area on chip and provides an excellent transient response. A novel voltage spike suppressor block is employed in the LDO architecture which reduces undershoot and overshoot of the output voltage during the abrupt load transition. It introduces a secondary negative feedback loop whose delay is lesser than the main loop and also steers the quiescent current to output node when required. This not only improves overall current efficiency but also reduces the on chip capacitance. The proposed LDO is laid out in 180 nm standard CMOS technology and post layout simulations are carried out. The LDO produces 0.9 V output when a minimum supply voltage of 1 V is applied. A maximum load of 0.5 mA can be driven by the regulator. The LDO exhibits 4.4 mV/V and 800 μV/mA line and load regulations respectively. When subjected to a step load change, an undershoot of 20.34 mV and an overshoot of 30.28 mV are recorded. For proper operation of the LDO, it requires only 4.5 pF on-chip capacitance.

A two-channel pulsed power supply for an imaging system with brightness amplification and independent synchronous laser illumination is designed. The power supply generates synchronized high-voltage pulses with a frequency of 16–24 kHz, an average electrical power of up to 1.2 kW, and an adjustable amplitude of up to 6.2 kV to pump copper bromide gas discharge tubes with independent control of the temperature parameters of the active medium. To generate pumping pulses for laser media, we used a two-channel thyratron circuit with a common source of stabilized voltage provided by a step-down pulse stabilizer and a bridge inverter-based circuit for the pulsed charge of storage capacitors. The voltage equalization on the storage capacitors is carried out by means of magnetic coupling of the charging inductances wound on a common core. Adjustable delay lines based on variable inductances provide synchronous operation of two brightness amplifiers with a synchronization accuracy of lasing pulses of ±1 ns. The power supply demonstrated stable operation with two gas discharge tubes having different characteristics, including those with different types of electrodes. It has been integrated into a laboratory facility for the study of high-energy materials combustion.

Increasing the penetration of distributed generation (DG) systems in power systems has many advantages, but it also has problems, including interference with the proper functioning of the protection systems. This problem is severe in microgrid systems that contain many DGs. Overcurrent relays are one of the most critical protection equipment of protection systems. The DG sources significantly change the characteristics of fault currents and the protection designs as well as the coordination of overcurrent relays. This paper proposes a coordination method for directional overcurrent relays with dual adjustment to resolve the interference problem in the protection system of a microgrid in the presence of distributed generation sources based on the electronic power converter (inverter). This is done by considering the curve of different standard characteristics according to the IEC60255 standard in two operating modes, the grid-connected and islanded. A genetic optimization algorithm is used to reduce the total operating time of the relays. The simulation results verify the effectiveness of the proposed coordination method. The results show that the protection coordination scheme with dual adjustment relays and the use of combined characteristic curves can significantly reduce the operating time of the total relays.

This paper proposes a robust H ∞ -LMI-based primary controller using the Linear Parameter Varying (LPV) modeling for an AC islanded Micro-Grid (IMG). The proposed controller can regulate the frequency and voltage of the IMG under various scenarios, such as load changes, faults, and reconfigurations. Unlike most previous studies that neglected the nonlinearity and uncertainty of the system, this paper represents the system dynamics as a polytopic LPV model in the novel primary control structure. The proposed method computes a state-feedback control by solving the corresponding Linear Matrix Inequalities (LMIs) based on H ∞ performance and stability criteria. The robust primary control is applied to a test IMG in the SIM-POWER environment of MATLAB and evaluated under different scenarios. The simulation results demonstrate the effectiveness and efficiency of the proposed method in maintaining the stability of the frequency and voltage of the IMG.

Rain attenuation prediction models are inevitably deployed to provide rough estimates of the actual measured attenuation due to severe scarcity in most of the tropical and equatorial climates. The results of rain attenuation measurements over a 14.8 GHz terrestrial microwave link and slant-path attenuation in vertically polarized signals propagating at 10.982 GHz in a tropical Malaysian climate were reported in this study. The experimental results including the path adjustment factors were compared with the predictions of some selected rain attenuation models. The relative errors in the path length adjustment factors (PLAFs) are in the range -0.3370 – 2.6272, while those of the slant path adjustment factors (SPAFs) are -0.9252 – +0.2923. Moreso, the charts of PLAFs and SPAFs at 0.01% of the time were also presented because they are the most commonly used availability by the telecommunications service providers. This study will allow the radio engineer to select the most suitable prediction models for the particular region under study, thereby ensuring adequate radio planning for improved service delivery especially in the tropical climates due to their peculiarity.

Grid-connected photovoltaic (PV) system is often needed whenever utilities fail to provide consumers with a reliable, sufficient and quality power supply. It provides more effective utilization of power, however, there are technical requirements to ensure the safety of the PV installation and utility grid reliability. In solar systems there is often excessive use of components, resulting in high installation costs. Consequently, appropriate measures must be taken to develop a cost-effective grid-connected PV system. An optimally sized PV system incorporated into an existing unreliable grid-connected commercial load for Mount Olive food processing is presented in this paper. The study focused on providing a reliable electricity supply which is cost-effective and environment-friendly. The techno-economic analysis of grid-connected PV/Diesel/Battery Storage systems was carried out using HOMER Pro software. Results showed that Grid/PV/BSS are technically, economically and environmentally feasible with the cost of energy at 0.136$/kWh and net present cost at $254,469. Also, the excess electricity produced by this combination is 13,264kWh/year, which generates income for the company by selling excess generated energy back to the grid if net metering were to be implemented. Furthermore, the CO2 emissions for these combinations decreased to 10,081.6 kg/year as compared to the existing systems (Grid/Diesel Generator) with emissions of 124,480 kg/year. This is an additional advantage in that it improves the greenhouse effect. A sensitivity analysis was carried out on the variation of load change, grid power price and schedule outages for the optimal system.

Demand-side management has become a viable solution to meet the needs of the power system and consumers in the past decades due to the problems of power imbalance and peak demand on the grid. This study focused on an improved decision tree-based algorithm to cover off-peak hours and reduce or shift peak load in a grid-connected microgrid using a battery energy storage system (BESS), and a demand response scheme. The main objective is to provide an efficient and optimal management strategy to mitigate peak demand, reduce the electricity price, and replace expensive reserve generation units. The developed algorithm is evaluated with two scenarios to see the behavior of the management system throughout the day, taking into account the different types of days (weekends and working days), the random profile of the users' demand, and the variation of the energy price (EP) on the grid. The simulation results allowed us to reduce the daily consumption by about 30% to 40% and to fill up to 12% to 15% of the off-peak hours with maximum use of renewable energies, demonstrating the control system's performance in smoothing the load curve.

Operation scheduling of a Virtual Power Plant (VPP) includes several challenges for the system according to the uncertain parameters, and security requirements, which intensify the need for more efficient models for energy scheduling and power trading strategies. Making suitable decisions under uncertainties, related to Renewable Energy Resources (RES), loads, and market prices impose extra considerations for the problem to make a clearer insight for the system operators to participate in local markets. This paper proposes a new risk-based hybrid stochastic model to investigate the effects of wind turbine power fluctuations on profit function, energy scheduling, and market participating strategies. Also, an incentivized Demand Response Program (DRP) is used, to enhance the system’s efficiency. The results of the study indicate that the proposed model based on Information Gap Decision Theory (IGDT) approach makes a clearer environment for the decision-maker to be aware of the effects of risk-taking or a risk-averse strategy on financial profits. The results show that a 30% of robustness and opportunity consideration would change the profit function from -12.5% up to 14.5%, respectively. A modified IEEE 33 bus test system is used to simulate a technical VPP considering the voltage stability and thermal capacity of line requirements.

Cost reduction, increased efficiency and reliability, extended service life, reduced noise and vibration, and environmental friendliness are critical for new generation wind turbines and electric vehicles. Segmented Hybrid Permanent Magnet (SHPM) machines, on the other hand, which are primarily segmented PMs combined with different materials, dimensions, and magnetization directions, offer a way to meet these needs. In this study, we present nine topologies of segmented PM-rotor SHPM generators based on the Taguchi experimental design method, while presenting a simple and accurate model based on subdomain method for estimating the magnetic performance characteristics of SHPM machines. An analytical model is provided. Magnetic partial differential equations (MPDEs) are represented in a pseudo-Cartesian coordinate system, and with appropriate boundary conditions (BC) and interface conditions (IC), the general solution and its Fourier coefficients are extracted using a variable separation approach. The performance characteristics of nine of the SHPM machines studied were compared semi-analytically and numerically. Two prototype SHPM machines were manufactured and semi-analytical modeling results were compared with finite element analysis (FEA) methods and experimental testing (load mode) on a generator. The FEA simulation and experimental test results have a maximum error rate of about 3, confirming the high accuracy of the provided semi-analytical model. We compare the induced voltage, torque ripple and magnetic torque among the investigated topologies.

In spite of the numerous benefits over the traditional power distribution system, protection of the microgrid is a challenging and complex task. The varying fault resistances due to dissimilar grounding conditions can affect the performance of the protection scheme. Under such conditions, the magnitude of the fault current can vary from lower to higher level. In addition to the above, the dissimilar magnitude of fault current during grid connected and islanded mode demands a protection scheme that can easily discriminate the mode of operation. The magnitude of fault current in grid-connected and islanded modes needs a robust protection scheme. In this regard, an ensemble of subspace kNN based robust protection scheme has been proposed to detect the faulty conditions of the microgrid. The tasks of the mode detection, fault detection/classification as well as faulty line identification has been carried out in the proposed work. In the proposed protection scheme, discrete wavelet transform (DWT) has been used for processing of the data. After recording the voltage and current signals at bus-1, the protection scheme has been validated. The validation of the protection scheme in Section 6 reveals that the protection scheme is efficiently working.