Recent Advances in Electrical & Electronic Engineering - Volume 14, Issue 4, 2021

Background: Immense growth in the field of VLSI technology is fuelled by its feasibility to realize analog circuits in μm and nm technology. The current mirror (CM) is a basic building block used to enhance performance characteristics by constructing complex analog/mixed-signal circuits like amplifier, data converters and voltage level converters. In addition, the current mirror finds diverse applications from biasing to current-mode signal processing. Methods: In this paper, the Complementary Metal Oxide Semiconductor (CMOS) technologybased current mirror (CM) circuits are discussed with their advantages and disadvantages accompanied by the performance analysis of different parameters. It also briefs various techniques which are employed for improvising the current mirror performance like gain boosting and bandwidth extension. Besides, this paper lists the CMs that use different types of MOS devices like Floating Gate MOS, Bulk-driven MOS, and Quasi-Floating Gate MOS. As a result, the paper performs a detailed review of CMOS Current mirrors and their techniques. Results: Basic CM circuits that can act as building blocks in the VLSI circuits are simulated using 0.25 μm, BSIM and Level 1 technology. In addition, various devices based CMs are investigated and compared. Conclusion: The comprehensive discussion shows that the current mirror plays a significant role in analog/mixed-signal circuits design to realize complex systems for low-power biomedical and wireless applications.

Background: With the advancement in the field of software development, software poses threats and risks to customers’ data and privacy. Most of these threats are persistent because security is mostly considered as a feature or a non-functional requirement, not taken into account during the Software Development Life Cycle (SDLC). Introduction: In order to evaluate the security performance of a software system, it is necessary to integrate the security metrics during the SDLC. The appropriate security metrics adopted for each phase of SDLC aids in defining the security goals and objectives of the software as well as quantify the security in the software. Methods: This paper presents a review and catalog of security metrics that can be adopted during the distinguishable phases of SDLC, security metrics for vulnerability and risk assessment reported in the literature for secure development of software. The practices of these metrics enable software security experts to improve the security characteristics of the software being developed. The critical analysis of security metrics of each phase and their comparison are also discussed. Results: Security metrics obtained during the development processes help to improve the confidentiality, integrity, and availability of software. Hence, it is imperative to consider security during the development of the software, which can be done with the use of software security metrics. Conclusion: This paper reviews the various security metrics that are meditated in the copious phases during the progression of the SDLC in order to provide researchers and practitioners with substantial knowledge for adaptation and further security assessment.

Background: Researchers have proposed a number of basic building blocks for various electronics applications. The current conveyor trans-conductance amplifier is one of them, which is suitable for linear as well as nonlinear applications of current and voltage mode circuits. Objective: This paper provides a review of the implementations proposed to date for the same with its applications in analog signal processing. The proposed possible applications of this device are also considered. Methods: Keeping in mind the utility of CCTA in low power VLSI application areas, a number of parameters like power consumption, operating voltage, 3dB bandwidth, trans-conductance, as well as a number of transistors used for implementation and technology are taken into consideration. Results: The results available for all the structures are compared and analyzed to investigate the potential advantages as well as disadvantages of this CCTA block and its limitations. Conclusion: This review concluded with a remark on the best suitable CCTA structure for low power applications and its future possibilities to use.

Background: Full adder is the key element of digital electronics. The CNTFET is the most promising device in modern electronics. To enhance the performance of the full adder, CNTFET is used in place of the CMOS. Objective: To implement the high speed full adder circuit for advance applications of the digital world. Methods: Full adder circuit with a new Gate diffusion technique has been implemented in this work. This is a comparative study of the 10-T CNTFET full adder with GDI technique and the 10-T Finfet based full adder using GDI technique. Ultra-low-power feature is the additional advantage of the GDI technique. This technology provides the full swing voltage to the circuit. Moreover, it also reduces the number of transistors required. This technique has been used with CNTFET to upgrade the full adder in terms of the dissipated power and product of power consumed and delay introduced in the circuit. Results: The proposed design shows that the low power dissipation comes out to be approximately 4.3nW at 0.5volts. The power delay product is 4.7x10-20 J at the same voltage level. The FinFET design also shows the better performance with GDI. But GDI enhances CNTFET based design power consumption by about 32% from the FinFET. Conclusion: CNTFET showed a better response due to good current conductivity as compared to the FinFET. This work has been implemented and simulated on the 32nm node technology.

Background: In the image processing area, deblurring and denoising are the most challenging hurdles. The deblurring image by a spatially invariant kernel is a frequent problem in the field of image processing. Methods: For deblurring and denoising, the total variation (TV norm) and nonlinear anisotropic diffusion models are powerful tools. In this paper, nonlinear anisotropic diffusion models for image denoising and deblurring are proposed. The models are developed in the following manner: first multiplying the magnitude of the gradient in the anisotropic diffusion model, and then apply priori smoothness on the solution image by Gaussian smoothing kernel. Results: The finite difference method is used to discretize anisotropic diffusion models with forward- backward diffusivities. Conclusion: The results of the proposed model are given in terms of the improvement.

Background: The present paper is based on models of conformable fractional differential equations to describe the dynamics of certain epidemics. Methods: In this paper, we have divided the population into groups, namely susceptible, exposed, infectious, and recovered, and also described the treatment modalities. Results: The analytical study of the model shows two equilibrium points (disease-free equilibrium and endemic equilibrium). Conclusion: For both cases, local asymptotic stability has been proven. In conclusion, we have presented the numerical simulation.

Background: In this article, an efficient direct method has been proposed in order to solve physically significant variational problems. The proposed technique finds its basis in Bernstein polynomials multiwavelets (BPMWs). The mechanism of the proposed method is to transform the variational problem into an algebraic equation system through the use of BPMWs. Objective: Since the necessary condition of extremization consists of a differential equation that cannot be easily integrated into complex cases, an approximated numerical solution becomes a necessity. Our primary objective was to establish a wavelet-based method for solving variational problems of physical interest. Besides being computationally more effective, the proposed approach yields relatively more accurate results than other comparable methods. The approach employs fewer basis elements, which in turn increase the simplicity, decrease the calculation time, and furnishes better results. Methods: An operational matrix of integration, which is based on the BPMWs, is presented. We substituted the approximated values of x , unknown function ξ (x) and their derivative functions ξ (x), ′ (x),..... ′ (x) with BPMWs operational matrix of integration and BPMWs. On substituting the respective values in the given variational problem, it gets converted into a system of algebraic equations. The obtained system is further solved using the Lagrange multiplier. Results: The results obtained yield a greater degree of convergence as compared to other existing numerical methods. Numerical illustrations based on physical variational problems and the comparisons of outcomes with exact solutions demonstrate that the proposed method yields better efficiency, applicability, and accuracy. Conclusion: The proposed method gives better results than other comparable methods, even with the use of a fewer number of basis elements. The large order of matrices, such as 32, 64, and 512, obtained by using other available methods is far too high to achieve accuracy in results in comparison to the ones we obtained by using matrices of relatively lower orders, such as 7, 8 and 13, in the proposed method. This method can also be used for extremization functional occurring in electrical circuits and mechanical physical problems.

Because of the consistently expanding demand of energy, the introduction of a decentralized microgrid based on energy resources will soon be the most exciting development in the power system. Microgrids (MGs), which are mainly based on inverters, are becoming more popular as they can handle different forms of renewable energy effectively. However, one of the most challenging areas of research is their control. In the last few years, many control strategies have been developed. In this review, different control methods have been discussed, applicable to the MG system. Furthermore, the comparative analysis of classical and modern control strategies is also considered. This survey guides the new researchers about all available control strategies and room for improvement towards the optimal solution of the MG control techniques. It also identifies several research gaps and future trends therein as well as provides a solution to manage problems in MGs. The strategies are then compared based on their applicability to different control requirements.

Background: Power distribution Internet of Things is a smart service system in which traditional distribution networks comprehensively apply modern computing technologies, such as cloud computing, mobile Internet of Things, and big data to realize the interconnection of all things in the power system and human-computer interaction. In the power distribution Internet of Things, there are many types of main power distribution equipment, and each type of power distribution equipment is connected with multiple sensor devices. These sensor devices play an important role in the smooth operation of the power distribution Internet of Things, so it is necessary to build a reliability evaluation system for these sensor devices. Objectives: The objective was to evaluate the reliability of the sensor device connected to the main equipment in the power distribution Internet of Things. Methods: Firstly, the G1-CV method (entropy weight method-coefficient of variation method) is used to construct the initial evaluation index system, and the comprehensive weight of each index is determined and ranked. Then the improved TriMap algorithm (ITriMap) is used to reduce the high-dimensional complex index system. Results: Simulation verification results show that the algorithm has a smaller reconstruction error than traditional dimensionality reduction algorithms such as t-SNE, Largr-Vias, UMAP, etc. The reduced index can scientifically and objectively measure the main equipment sensors of the power distribution network. Conclusion: An index reduction method based on the ITriMap algorithm is proposed to evaluate the reliability of sensors. Experimental results show that this algorithm greatly reduces the reconstruction error compared to other traditional methods. Discussion: In the future, on the basis of this article, we intend to construct a sensor reliability evaluation model for the main equipment of the power distribution Internet of Things using the 5- dimensional features after dimensionality reduction as input.

Background: With respect to the problem of wind power and photovoltaic (PV) gridconnected accommodation, a power system optimization dispatching method is proposed that introduces a concentrating solar power (CSP) station to promote wind power and PV accommodation, considering the dispatch-ability of the thermal storage system (TSS) and the accommodation capacity of the electric heating device (EHD) in the CSP station. Methods: The method analyzes an internal simplified model of a CSP station and a short-timescale identification method of wind and PV power ramping events based on a CSP-Wind-PV system structure. Furthermore, the operating characteristics and constraints of various units are considered with the goal of the lowest comprehensive system cost to establish a CSP-Wind-PV optimization model for dispatching power system. Results: The method is simulated and verified on the IEEE-RTS24 node system by using the MATLAB optimization toolbox. Conclusion: The results demonstrate that the participation of a CSP station can decrease the number of power ramping events and reduce the curtailment of wind and PV power while ensuring the economical operation of the power system.

Background: This study aims at solving the problems of large design size and insufficient number of the notched band for traditional ultra-wideband (UWB) filters. A planar compact microstrip UWB bandpass filter (BPF) with quad notched bands and good selectivity is proposed using a modified multiple-mode resonator (MMR) and defected ground structure (DGS). Methods: The MMR consists of a stepped impedance stub above and two pairs of open-circuited stubs on both sides, which can generate the passband and double notched bands of UWB filter, the other two notched bands are obtained by DGS. Results: The UWB filter with quad notched bands respectively centered at 3.9 GHz, 5.7 GHz, 7.9 GHz, and 9.8 GHz is fabricated and measured. Conclusion: The measured results are basically consistent with the simulated results, which proves the correctness and practicability of the UWB filter.

Objective: In this paper, an optimal control scheme for the Interlinking Converter (IC) system is achieved by the proper regulation of its gate switching functions through appropriate optimal feedback controller design. Methods: Proportional-Integral-Derivative (PID), Fractional Order Proportional-Integral-Derivative (FOPID) and H-infinity loop shaping controller have been designed for the two-fold control objective of simultaneous improvement in system robustness and reduced tracking error using parameter tuning via Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) optimization algorithms. Results: The controller parameters are obtained by optimization algorithms. The comparative analysis of the controller performance is carried out through simulation in the MATLAB platform to validate the effectiveness of the controller design under various changing situations. Conclusion: The optimized controller parameters obtained through ABC algorithm are better than that obtained through PSO algorithm in terms of both objective function values and execution time. The resultant robust control strategy for IC system obtained through the H-infinity loop shaping controller provides reduced tracking error and improved stability as compared to PID and FOPID controller, as proved by the simulation results.

Background: The present paper compared two methods that are employed to determine the fault location in VSC-HVDC transmission lines. These systems are widely recognized for their fast and reliable control. Methods: Wavelet transform was employed as an advanced technique of signal processing to extract important characteristics of fault signal from both sides of the line by phasor measurement unit (PMU). Deep Learning was implemented to identify the relationship between the extracted features from the wavelet analysis of fault current and variations under fault conditions. Wavelet transform and advanced signal processing techniques were adopted to extract important features of fault signals from both sides of the line by PMU. Results: The results indicated the high accuracy of finding fault location by the deep learning algorithm method compared to the k-means algorithm with an error rate of <1%. Conclusion: Studies on the 50 kV VSC-HVDC transmission line with a length of 25 km in MATLAB have been conducted.