Scanning the Issue

There are a total of seventy articles (70) included in this month's volume of the IETE Journal of Research (Vol. 69, No. 5, May 2023). In the following articles, ongoing studies and new developments in the fields of biomedical engineering, power systems, electromagnetics, computer science, electrical and electronics engineering, and microelectronics are discussed.

In the first paper of the issue, titled “Comparison of Heuristic Approaches in Weight Optimization of Different Power Levels Transformer,” the weight of widely used distribution type transformers and power transformers is optimised. The Firefly algorithm, the Ant Colony algorithm, and the Bee algorithm are used in an heuristic way to figure out the weight of transformers. Optimization of the iron weight components that have the most effect on the weight of a transformer made in more than one type is given. The goal is to lower the cost of the transformer, make it last longer, and make it more efficient by getting the best numbers for the current density (s) and iron section (C), which are the variables used to figure out the iron weight of the transformer. Heuristic optimisation techniques outperformed standard methods in the study. Heuristic optimisation yields the best weights for 50 kVA and 1000 kVA transformers, enabling lower transformer designs.

The second paper, titled “Design and Analysis of Zeta Converter for Power Factor Correction using Cascade PSO-GSA Tuned PI and Reduced-Order SMC” describes a single-phase power factor correction method employing a DCDC Zeta converter in continuous conduction mode.To increase converter performance, it presents a non-linear cascade control of particle swarm optimization-gravitational search algorithm (PSO-GSA) tuned proportional-integral and sliding mode controller in outer and inner loops. Compared to prior methods, the suggested control strategy improves power factor, reduces overall harmonic distortion, and tracks output voltage for reference voltage changes more efficiently. For solar photovoltaic battery charging, the proposed technique is tested. Real-time hardware implementation of the DC-DC Zeta converter verifies simulation results.

In the next paper, “High Speed Hybrid Multiplier Design using Hybrid Adder with FPGA Implementation,” a hybrid parallel adder-based multiplier is proposed to make multiplying faster than the current method. With the help of a hybrid adder (Hancarlson, Weinberger and Ling adder), the partial products of each pair of consecutive bits (the multiplicand) are added together at the same time in this method. Xilinx ISE 12.1 and different FPGA boards are used to synthesis and simulate the proposed architecture. The compiled report reveals that the suggested multiplier is faster than alternative possibilities, such as the Array multiplier, the Wallace tree multiplier, the Multiplier that uses a compressor, the Vedic multiplier, the modified Booth multiplier, etc.

In the following paper, “Performance Investigation of a Modified Hybrid Parallel Prefix Adder for Speedy and Lesser Power Computations,” the authors explain how modern portable systems, especially deep learning applications, require high-speed, low-power big operand adders and how parallel-prefix quick adders consume a lot of power for large operands. Modern consumer electronics demand a different design. Big parallel-prefix adders with hybrid adders create the least significant carriers faster than the most significant ones. This paper customises the binary to Excess-1 Converter (BEC) and makes Cin=1 in the standard Carry Select Adder (CSA) to save power and space instead of using RCA. BEC lowers logic gate counts. Customized BECs boost Kogge stone-Ripple carry adder efficiency(KS-RCA). All current and future adder implementations use Cadence tool RTL compiler with 90 nm TSMC technologies. The proposed method reduces latency by 76.39%, 70.86%, and 3.27% compared to CSEL-BEC, CSELRCA, and KS-RCA. KS-RCA, CSEL-RCA, and CSEL-BEC use 28.92%, 10.61%, and 11.06% less power. However, the proposed approach efficiently reduces area by 29.52%, the highest value among implemented techniques.

The authors in their paper “Hybrid Cuckoo Search with Clonal Selection for Triclustering Gene Expression Data of Breast Cancer” use triclustering to extract co-expressed genes across samples and timeframes. Clonal selection creates cuckoo eggs. The suggested study finds the top breast cancer-associated tricluster genes. Hybrid cuckoo search with clonal selection outperforms traditional cuckoo search and other triclustering techniques.

The paper “A Comprehensive Review on Supply Modulators and Control Strategies for Envelope Tracking RF Power Amplifiers in Mobile Communication” discusses efficiency enhancement methods for back-off RF power amplifiers. It examines the power supply modulator architectures for envelope tracking power amplifiers.The hybrid supply modulator control techniques are included. Hybrid supply modulators' state-of-the-art work is also summarized in the study.

In the paper, titled “On New Transmission Line Puzzles,” the author begins with a brief description of the well-known paradox of lossless transmission lines and then demonstrates how this paradox can be overcome by removing the loss-free requirement. In addition, some new, unsolved Transmission Lines puzzles are introduced.

In the article “ANFIS-based Power Quality improvement by Photovoltaic Integrated UPQC at Distribution System,” a photovoltaic unified power quality conditioner system is presented and analyzed with an Adaptive neuro-fuzzy controller and a reinforced learning algorithm. The Fuzzy-Model-Based controller infers system parameters using linguistic principles to optimize system performance and reference current generation. This system works successfully under varying loads. Adaptive Neuro-Fuzzy Inference Systems reduce total harmonic distortion.

In the next article, titled “Performance Evaluation of RSM and ANFIS in Modeling Nano Fluids-based Mixed Insulating Fluids,” the prediction of dielectric strength, fire point, and viscosity through response surface methodology (RSM) and adaptive neuro-fuzzy inference system (ANFIS) is developed to improve the liquid dielectric lifetime in an automated environment. Experiments with three independent input parameters were prepared using a box-behnken experimental design based on the RSM. The comparison results demonstrates that the developed ANFIS model is an effective instrument for modeling nanofluid-based mixed insulating fluids.

The authors apply a new Chua's chaotic circuit, a basic combination of electronic components that shows chaos, in the next paper, “Analysis of Fourth-order Chaotic Circuit based on the Memristor Model for Wireless Communication,” based on the Hewlett-Packard memristor. Chua's circuit uses an active memristor based circuit with a negative resistor and TiO₂ based memristor to exhibit chaos without scaling the differential equations and produce realistic voltages and currents across the circuit components. For the first time, Chua's circuit using memristors and physical equations produces chaotic oscillations. The single memristor-based chaos is analyzed. Such a circuit is useful in chaos-based systems for wireless communication.

This paper titled, “CMOS Implementation of a Novel High Speed 4:2 Compressor for Fast Arithmetic Circuits” examines the design and analysis of a new 4-2 compressor for high-speed multipliers. By optimising the width of the transistors, C_out can be generated more rapidly, allowing for higher operating speeds. The effect of process variation on the circuit has been examined in this work , and a new structure is proposed to counteract this effect. Using these compressors, a 32x32-bit multiplier is created to evaluate the novel compressor in a practical setting.

In the subsequent paper “Performance Analysis of Glioma Brain Tumor Segmentation using CNN Deep Learning Approach” author suggests using Convolutional Neural Networks (CNNs) as a classification method for segmenting Gliomatumour regions in brain MRI images. To improve the abnormal pixels relative to the surrounding pixels in an MRI of the brain, the adaptive histogram equalisation technique is used. The Gabor transform is used to convert the improved brain picture into a multi-directional scaling image. In order to distinguish a Glioma from a typical brain MRI, features are extracted from the multi-directionally scaled image and then trained and classified with a CNN deep learning algorithm. At last, morphological procedures are used to segment the tumour areas.

In their paper titled “Robust Adaptive Control of a Quadruple Tank Process with Sliding Mode and Pole Placement Control Strategies,” the authors develop and assess an Adaptive Pole Placement Controller and a robust Adaptive Sliding Mode Controller (ASMC) for high-efficiency control of a minimum-phase Quadruple Tank Process. Due to the parameter estimation method utilised in the design processes, simulation results demonstrate that the proposed adaptive control configurations outperform the PID controller with lower performance indices and quicker settling periods. The results demonstrate that a decentralised ASMC can be utilised to enhance the speed and robustness of a variety of multivariable industrial process control systems.

The paper, “Wavelet Sub-bands Features-based ECG Signal Quality Assessment Scheme for Computer-aided Monitoring System,” suggests an efficient SQA scheme that avoids R-peak features and machine learning-based ECG SQA approaches. Wavelet transform (WT) frequency localisation recovers sub-band features. Machine learning classifiers use traits to assess data quality. The proposed method's evaluation accuracy is 98.11% on the simulated dataset, 99.12% on the single channel ECG dataset from Physionet's Computing in Cardiology Challenge (PCinCC), and 97.32% on the real arrhythmia dataset from MIT-Beth Israel Hospital database (MITDB). An extensive study shows that the ECG SQA method can enhance computer-aided automated cardiac monitoring systems.

In the paper “Miniaturized Dual-Band Metamaterial Loaded Antenna for Heterogeneous Vehicular Communication Networks,” the authors design a dual-band monopole antenna that operates at two distinct frequencies, namely 2.45 GHz and 3.6 GHz, and is suitable for ISM and WLAN/WiMAX communications in an automotive environment. Using a 3D vehicle model, the suitability of the proposed antenna for heterogeneous vehicular communications is validated through simulation. It is investigated how the vehicle's structure affects the radiation pattern. The prototype antenna is manufactured, and the simulation results are validated through experimental measurements.

The authors in the next paper, titled “Design of Mettalic via based Octo-port UWB MIMO Antenna for I_OT Applications” suggest a compact Ultra-Wideband (UWB) MIMO antenna with eight ports and a metallic via (M-Via) base for Internet of Things use. Reflection coefficient, mutual coupling, peak gain, radiation pattern, and radiation efficiency are some of the antenna characteristics studied. They conduct an experimental investigation of key MIMO factors like ECC, DG, TARC, and CCL. The suggested antenna is also shown to work in a real-time environment.

In the paper “Performance Evaluation towards Automatic Building and Road Detection Technique for High Resolution Remote Sensing Images,” the authors create a way for high-resolution satellite images to automatically find buildings and roads. They use Internal Gray Variance (IGV) to find houses and roads in cities. Morphological operators are used to improve the satellite pictures. Using the differences in the grey levels, the Multiseed-based clustering method can find the edges of the building and the road. The authors test the system on a large number of freely available road and building detection data sets.

Detecting R-peaks is now a key part of automating the diagnosis of serious heart illnesses.This article called “R-Peak Identification in ECG Signals Using Pattern Adapted Wavelet Technique,” aims to improve the accuracy of R-peak detection by using a new pattern-adapted wavelet that cuts down on false positives and detection errors. The results of the experiments show that the proposed pattern-adapted wavelet method works better than Symlet4 and other existing methods.

In the paper “Development of a Compact Electrical Impedance Measurement Circuit for Protein Detection Two-Electrode Impedance Micro-Sensor,” an electrical impedance measurement circuit board is made for use in protein preconcentration and detection microfluidic chips with an integrated two-electrode impedance micro-sensor. On the circuit board, a lock-in amplifier is used to measure the impedance curve between 10 and 200 kHz. The results allow for a possible method to be used in diagnostic uses at the point of care.

Next paper “Fault-Tolerant Based Group Key Servers with Enhancement of Utilizing the Contributory Server for Cloud Storage Applications” uses centralised key management-based grouped structure. Centralized cloud user and group keys are generated by the Key Server. The proposed work's Central Server and sub-servers manage numerous groups. Each group has many fault-tolerant sub-servers. Users are limited. Each group uses a central server and a key to avoid internal threats. The planned work improves intergroup communication and central server calculations and storage. Maintaining a file access list for each file eliminates the rekeying process for new users and reduces security features even if the group key slips after the user leaves. This paper proposes contributory key management, where each member creates the group key.

The authors of the paper “SMOTE: An Intelligent SDN-based Multi-Objective Traffic Engineering Technique for Telesurgery” propose a new multi-objective Traffic Engineering (TE) technique called SMOTE to ensure QoE for telesurgery applications running on a Software Defined Network. This article aims to help network administrators give remote surgeons a good quality of experience (QoE) during remote procedures. The suggested approach takes into account the goals of minimising end-to-end delay and packet loss. As predicted by simulation findings, SMOTE ensures QoE in telesurgery.

The next paper, titled “Impact of PLL and Virtual Inertia on Deregulated AGC System Integrated with parallel AC/HVDC” examines how phase-locked loop (PLL) systems and virtual inertia impact a deregulated parallel AC/HVDC tie-line integrated two-area automatic generation control (AGC) system. Thermal and hydrogas components of the multi-area AGC system are Area-1 and Area-2. An attempt is made to utilize a new secondary controller named the two-degree-of-freedom tilt-integral-derivative (2DOF-TID) controller. A new meta-heuristic method, the bird swarm algorithm (BSA), optimises gains and PLL parameters. 2DOF-PID outperformed the planned 2DOF-TID controller in system dynamics. Simulated inertia shows that the AC/HVDC tie-line with PLL outperforms the other two choices in system dynamics. Studies suggest that the response obtained at the nominal value of natural frequency (ω n) and damping coefficient (ζ) reduces the subsequent oscillation and offers superior dynamics compared to varying conditions,and the effect of variation in PLL parameter on the system dynamics is also analysed.

The next research paper, “Synergy of Electrical Pulses and Black Pepper (Piper nigrum) extracts for Effective Breast Cancer Treatment: An In vitro Model Study” investigates the efficacy of electrical pulse-mediated Piper nigrum extracts against ER-positive MCF-7 human breast cancer cells. It was discovered that electrical pulses facilitate the production of antioxidant and phenolic-rich extracts. In addition, this treatment is more suitable for achieving maximal cell death with a lower concentration of the extract for breast cancer treatment.

This paper on “Dual Band Dual Linear Polarized Equal Cross Track Beam Microstrip Antenna for Airborne SAR” presents a design of a common aperture dual band dual linearly polarised microstrip array antenna for aerial synthetic aperture radar(SAR) at L and S bands. Both bands' beamwidths are optimised for the antenna. The probe-fed square circular patch antenna at L-band and the electromagnetically-coupled stacked patch antenna at S-band are placed in 2x6 and 2x12 arrays on the same aperture. A small antenna facility built and tested it. The 1:2 VSWR bandwidths are obtained at L-band 200MHz and S-band 400MHz. Peak gain is 16.3 dBi at 1.25 GHz and 19.0 dBi at 3.2 GHz. Both frequencies have cross-polarization and isolation higher than 30 dB.

Next paper “Single VDTA-Based Tunable Floating Lossy Inductance Simulation Circuits” proposes two circuit topologies for emulating tunable lossy floating inductors. Each simulator uses one voltage differencing transconductance amplifier (VDTA) and two passive elements with a grounded capacitor. PSPICE simulations and experimental data prove all proposed circuits work. A fourth-order equal-ripple low-pass filter and an electrically tunable sinusoidal oscillator are built to test the inductor designs.

The authors of ”RNS Comparison via Shortcut Mixed Radix Conversion: The Case of three 4-Moduli Sets $2^n,2^{n\pm 1},2^{(n+1)-1},2^n,2^{n\pm 1},2^{(n+1)+1}$, and $2^n,2^{n\pm 1},2^{(n-1)-1}$,” provide more accurate residue number systems (RNS) comparators for three balanced 4-moduli sets using this method. Significant gains in several measures of merit can be seen in the synthesis findings. For the first moduli set, for instance, a 29% (24%) speedup (cost reduction) is accomplished, while the second set's cost is reduced by 18%, power dissipation is reduced by 28%, and energy consumption is cut by 64%.

The following article, titled “A Partially Filled Shorted Coaxial Line Technique for Material Relative Permittivity Determination,” describes an extraction technique for material relative permittivity based on three measurements of two identical coaxial lines terminated by a short circuit configuration. Within the frequency range of 6-20 GHz, the precision of the relative permittivity parameter is greater than 5%. All samples analysed have been compared to the two transmission-line technique outcomes.

“Handwritten MODI Character Recognition using Transfer Learning with Discriminant Feature Analysis” is the next article, This paper creates a MODI handwritten character image dataset and a supervised Transfer Learning (TL) classification system. It transfers weights from pre-trained Deep Convolutional Neural Networks (DCNN) Alexnet to update the network. This network extracts features from network levels. Classifier models are obtained on activation features using an SVM. Recognizability and feature analysis are examined with these models. Selecting discriminant deep features uses subjective and objective metrics. Handwritten MODI and Devnagari character detection accuracies consisted 92.32% and 97.25%.

The following paper “Enhanced Facial Emotion Recognition by Optimal Descriptor Selection with Neural Network,” develops a smart FER model. Face extraction, image filtering, facial component extraction, and descriptor selection and categorization comprise the proposed model. First, the Viola-Jones object detection method is used to extract the face from the input picture. Gabor Filtering also filters noise. Then, the Affine-Scale-Invariant Feature Transform (ASIFT), a SIFT variant, extracts facial traits. The optimal descriptor selection method uses MV--WOA, a hybrid metaheuristic algorithm, to reduce the amount of ASIFT-generated descriptors due to their length. Extractions undergo neural network (NN) analysis. The WOA+MVO algorithm optimises NN hidden neuron count. The developed system beats state-of-the-art emotion recognition methods on seven emotions: neutral, happy, sad, surprise, angry, fear and disgust.

This work in the paper, titled “Performance Evaluation of Sub 5 nm GAA NWMBCFET using Silicon Carbide Source/Drain Material’ ” compares a cylindrical Gate All Around Nano Wire Field Effect Transistor (GAA NWFET) and a cylindrical Gate All Around Nano Wire Multi Bridge Channel Field Effect Transistor (GAA NWMBCFET) with gate lengths of 35 nm and 5 nm, respectively. Multi bridge channels and SiC boost current flow. Each device's current-voltage properties are plotted. Electron motion and “Subthreshold Swing” are assessed.

The next paper is “Robust Control of Nonlinear Fractional-order-Systems with Unknown Upper Bound of Uncertainties and External Disturbance.” This work examines nonlinear fractional-order system asymptotic stability when outside disturbances and uncertainties have undetermined upper limits. Uncertainties are limited by a pseudostates norm nonlinear function with unknown coefficients. Robust fractional-order sliding mode control stable a nonlinear fractional-order system with unknown upper limits on external shocks and uncertainties. Adaptive control rules estimate external disturbances and uncertainty. The Lyapunov theorem always shows that the sliding surface converges to zero, proving the system is stable. A good moving surface also solves chattering. Finally, real-world examples demonstrate the fractional-order controller's effectiveness. Modeling shows that the suggested controller functions well even with external disturbances and uncertainties.

High-density image tracking from video sequences may discover and categorise crowds, according to the research shown by the authors in “Novel Approach by Fuzzy Logic to Deal with Dynamic Analysis of Shadow Elimination and Occlusion Detection in Video Sequences of High-density Scenes.” In reality, shadows in video scenes cause problems with detecting or understanding what is happening. In this paper, the authors describe an automatic system for getting rid of shadows based on extracting the vector size of the movement and detecting occlusion management with the Fourier series approach due to the position and orientation of the camera, speed magnitude and visual tracking of crowd scenes, and mathematical morphology of discrete data in a non-linear way. To prove that their method works, they have dealt with the problem of vehicles blocking the view and used Benchmark data from 2009. The model is built of real elements that can be distinguished from combined data and a shadow-filled scene that makes it difficult to count and evaluate automobiles and people.

In the next paper, “MillimeterWave High-Gain Antenna Array for Wireless Applications,” authors argue that fourth-generation (4G) wireless technology must be upgraded to fifth-generation (5G) to meet the growing demand for data rate, coverage, and spectral efficiency. To eliminate delay and latency, 5G technology has a data rate greater than 1 Gbps. A well-implemented array boosts 5G technology.

The following paper “Design and Analysis of Junctionless-based Symmetric Nanogap-Embedded TFET Biosensor” investigates symmetrical dual material double gate dielectric modulated junctionless TFET (DM DG JLTFET) for use in biosensors. The JLTFET is composed of Si with a heavily doped n-type substrate. The JLTFET employs dielectric modulation to assist the bio-transistor in distinguishing between neutral and charged analytes (biomolecules). In order to reduce the effect of limited channels on device properties, a twin metal gate configuration employs two distinct metal gate electrodes. The nanogap cavity of the device immobilises biomolecules. The surface potential and sensitivity of neutral and charged-neutral analytes are examined. Simulations investigates the effects of nanogap region length and fill-in factor. The investigation explores the behaviour of DM DG JLTFETs for sensing biological molecules using relative permittivity and charge density. This study examines structural geometry variables that affect biosensor sensitivity, including cavity length, thickness, and fill-in factor.

In this paper, titled “Numerical Study of Two HEMTs AlGaN/InGaN by Sharing the Drain Area for Power Application” authors use Silvaco-Tcad software to simulate a high electron mobility transistor structure with two HEMTs that share the drain. The two HEMTs, AlGaN/InGaN on H4-SiC substrate with 50 nm gate length, work well in many different uses. It has a drain current of around 991.4 mA, a maximum transconductance of 859.1 ms/mm at Vds = 3V, a cut-off frequency of 115.6 GHz, a maximum oscillation frequency of 168.8 GHz, a drain-induced barrier lowering (DIBL) of 40 mV/V, a subthreshold swing of 130 mV/dec, an On/Off current ratio of more than 6 and a leakage gate current of 2x10⁻⁸ A.

Microgrid solar photovoltaic (PV) arrays have multiple strings connected in various ways. The paper on “String Fault Detection in Solar Photo Voltaic Arrays” investigates a line's failure. To analyse microgrid system inverter output currents, they were measured. Fast Fourier Transformation (FFT) was used to calculate DC components and THD. Skewness and kurtosis were employed to analyse discrete wavelet transformation (DWT)-based inverter output current coefficients. These studies were conducted under normal and string fault conditions. At certain DWT levels, string difficulties with DC components, THD, kurtosis, and skewness are related. The parameters have been chosen, and an algorithm for string fault detection has been proposed. The strategy works in real system data case studies.

Wind farm plan optimization or WFLOP, is a difficult optimisation problem with many constraints. In this paper, titled “Large Wind Farm Layout Optimization using Nature Inspired Meta-heuristic Algorithms,” authors demonstrate how the biogeography-based optimisation (BBO) algorithm may be utilised for big WFLOP and compare its performance to that of the genetic algorithm (GA), particle swarm optimisation (PSO), and ant colony optimisation (ACO). A modified cost of energy fitness function measures success in 25 wind farm scenarios. More statistical conclusions have been drawn using 99% Confidence Intervals and Student's t-test. For the same number of rounds, BBO yields greater fitness function values than the other algorithms. PSO takes the longest, GA the shortest.

The work of the paper “Robust Guaranteed Cost-Control for Half-Vehicle Active Suspension Systems Subject to Markovian Controller Uncertainties,” proposes a guaranteed-cost, robust controller for a half-vehicle active suspension system (HVASS) with stochastic controller gain variations. Due to poor assembly and deteriorating parts, the controller is inconsistent. This approach's state-feedback controller uses Markovian gains. An optimal multi-mode design technique bound by H₂ norm restrictions ensures asymptotic stability with a predetermined disturbance attenuation. Linear matrices inequalities (LMIs) govern this Lyapunov-based system. It enhances HVASS dependability and is readily reducible to systems with well-implemented controllers. Simulations and comparisons indicate the strategy's viability.

The authors of next paper, titled “Robust Load Frequency Control Using Fractional-Order TID-PD Approach via Salp Swarm Algorithm” proposes a dual-stage load frequency control (LFC) system using a fractional-order tilted integral-derivative (TID) controller and an integer-order proportional-derivative (PD) controller. The salp swarm approach fine-tunes the controller's parameters. The tilted-integral-derivative controller's fractional-order framework makes the scheme robust and quick at disturbance rejection, while the proportional-derivative controller improves transient response. The LFC performs better with the thyristor-controlled phase shifter (TCPS) and redox flow battery (RFB) components. The suggested control technique uses multi-area, multi-source power systems with thermal, hydro, and wind turbine units with nonlinear functions including generation rate constraint (GRC), governor dead band (GDB), and communication delay (CD). Simulation findings reveal that the recommended control approach regulates frequencies better with and without TCPS and RFB than the recently developed LFC methods. Sensitivity study confirmes the control method's robustness.

In the paper “An Accurate Hybrid Approach for Electric Short-Term Load Forecasting” authors suggest an accurate approach for Short-Term load forecasting (STLF) for efficient working of power system. The effects of weather conditions like temperature, humidity, dew point, wind chill, and wind speed on load forecasting are studied in terms of Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), and Maximum Error (ME) errors to improve forecasting accuracy. The hybrid method uses SVR and fuzzy because SVR can generate predictions with minimal data sets and fuzzy systems can handle nonlinear weather conditions and uncertainty in load forecasting. Load projections take into account the time of day, the preceding month's hourly load, the weather, the last ten calendar days, the quantity of sunshine, the temperature at the same time the day before, and the average temperature of the last three hours. Whether it's a weekday or a holiday, the suggested strategy predicts load accurately. Only the last month's days are utilised for load forecasts, and weekends aren't treated differently. The suggested strategy is tested using EUNITE network data from 1997 and New England of America data from 2012 and 2019.The suggested method outperforms ANN, Bayesian, Least square SVM, and other algorithms for estimating daily load.

Individuals experiencing knee joint pain (arthritis) and in the early phases of recovery might benefit greatly from an understanding of how the knee moves, as is discussed in this paper, “Nanocomposite Piezoresistive Pressure Sensor in Gait Monitoring for Arthritis Patient.” Knee joint issues are treated by monitoring knee joint pressure changes. Wearable devices are usually better for this. This work uses a CNF (Carbon Nano Fiber) and TPU (Thermoplastic Polyurethane) nanocompositepiezo-resistive (20% w/w) sensor film with a bulk resistivity of 192Ω-cm to build up the detecting mechanism in a patella packaging. It is also tested to see if it can track knee pressure-induced resistance changes. The continuous voltage shift during compressive stacking lab testing shows that this piezoresistive material has several uses. Thus, it can track arthritis sufferers' knee movements via signal collection techniques.

"Heuristic Topology for Designing Reconfigurable Balun Active Filter for Frequency, Bandwidth, and Power Division Ratio” describes this unique balunbandpass adjustable active filter. A matched amplifier connects the last stages. The construction uses a three-stage balun filter with 13% fractional bandwidth (FBW). A balun filter can be customised by replacing balanced port loss with an active device. The unit compresses from 77mm to 42mm and can be customised for operating frequency, bandwidth, power division ratio (PDR), and broad band stop response. The amplifier fits in the second loop without the balun filter. MWO AWR simulations showed that the balun filter's gain fluctuates by 11 dB between Ids=52mA and Ids=78mA. Active balun filters use RT Duroid. S₁₁ is less than -15 dB from 1.9 GHz to 2.18 GHz, confirming the simulations. Adjusting gain to change frequency, bandwidth, and PDR is novel.

The authors' paper “A Comprehensive Review of High-frequency Transmission Inverters for Magnetic Resonance Inductive Wireless Charging Applications in Electric Vehicles” details the design of high-frequency inverters used in inductive power transfer (IPT) applications in electric vehicles. This research examines an electric car's high-frequency inverter for inductive power transfer (IPT). The literature focuses on coil size and shape to transfer a lot of power with existing topologies. IPT magnetic resonance coupling works due to the resonance effect. The matching network's resonance frequency must match the inverter's. This study investigates remotely charging electric car inverter topologies.

The next paper “Data Augmentation for Improved Brain Tumor Segmentation” discusses how deep neural networks (DNN) need huge preprocessed samples of training-annotated pictures to train. This makes biomedical imaging pricey. Researchers employ data augmentation to improve training data and teach the network homogeneity and robustness. Most training systems' capabilities and output accuracy are significantly limited by traditional data enhancement methods. This research proposes generative adversarial network (GAN)-based automatic data augmentation to create high-quality brain cancer images. This improves deep learning with less preprocessed samples. The tumour was divided utilising a level set method and geodesic active contour. The approach was tested using BRATS13 MRI brain pictures of various sorts. Simulations yielded 0.942 dice similarity coefficients.

The research on “A Novel Method for Stride Length Estimation Using Wireless Foot Sensor Module” presents a new method for calculating stride length (SL) from a wireless foot sensor module (WFSM) with an inertial sensor. Stride length difference is a clinically relevant spatial gait metric. This study proposes measuring foot slope and WFSM single-axis acceleration to calculate SL. The foot slope angle finds gait events and accounts for gravity to determine foot speed. This approach simply requires foot angle, path, and sagittal plane speed. A healthy group checks the data against a common gait analysis instrument. To evaluate results for walking outside, 10 healthy individuals' trial data was examined. The approach might measure real-time walking.

In the next paper, “Modeling and Performance Improvement of Fractional Order Band-Pass Filter Using Fractional Elements,” it is explained how fractional-order circuits can be used to find the best way to look into the filter's parametric response. In this work, a model and performance of a band-pass filter with a fractional order are improved. To analyse the fractional-order bandpass filter, one needs a fractional-order capacitor (FC) and an inductor (FI) with a certain range. Simulation gives the frequency values of the proposed band-pass filter with an order between α and β. From the results of the fractional-orders α and β and for the given FC and FI, the quality factor is optimised. The theoretical quality factor of this integer-order filter is compared to the optimised Q value of its fractional-order counterpart. Models of the suggested filter are made using the best orders of α=0.4 and β=1.0 for FC and FI, respectively with optimized Q-factor. Finally, the frequency parameters of the filter as modeled are obtained through simulation using MATLAB/Simulink R2011a.

India's nuclear research reactors can irradiate core structural materials to assess radiation damage is explained in the next paper by the authors of “Design of Temperature Controller for Irradiation Experiment in Nuclear Reactor”. The temperature-controlled instrumented irradiation capsule (TCIIC) simplifies reactor-based sample irradiation. This study designs a TCIIC PID controller to manage temperature. Positioning the dominant pole-zero in the “S-plane” estimates PID controller parameters in a stable zone. Time responses from the recommended method have been compared to those from other, more well-known PID controller design methods and proven experimentally. The irradiation experiment shows that the controller settings can provide consistent and reliable temperature control.

In the next paper, “Small Dual-Narrow band BPF with Ultra-Rejection band Using Grounded Stepped Impedance Resonator,” authors present a simple method for designing a dual narrow-band bandpass filter with wide stopband performance based on a grounded stepped impedance resonator (GSIR). After the even-odd analysis, the proposed GSIR generates the passband centre frequencies. To determine filtering response, two ring-shaped stubs are electrically coupled to the low impedance region of the GSIR utilising coupling space (s) and directly attached to the input/output ports. Finally, a 2.4 GHz WLAN and 3.5 GHz WiMAX experimental filter is built. Simulated and measured filtering characteristic performance is compared and analysed. Thus, super high frequency suppression above 20 GHz generates two narrow bandwidths of 40 MHZ at 2.4 GHz and 60 MHz at 3.5 GHz. The intended filter has a very small surface area—about 56 mm 2—where the feeding ports end.

The authors of “Kapur's Entropy based Hybridised WCMFO Algorithm for Brain MR Image Segmentation” proposes a Kapur-based hybridised WCMFO approach that blends moth flame optimisation (MFO) with a water cycle algorithm (WCA)for brain MR image segmentation multilevel thresholding. Khalilpourazari and Khalilpourazary's WCMFO algorithm combines WCA and MFO's greatest features to produce faster convergence and higher exploration and exploitation capabilities than any other technique. Kapur entropy was utilised as the objective function in a series of studies with ten axial, T 2-weighted test photos and a threshold range of m=2-5. The water cycle algorithm uses moth spiralling to get the global optimum. WCMFO objective function value, PSNR, CPU time, and standard deviation are compared to other AWDO, ABF, and PSO algorithms. The hybridised WCMFO algorithm outperformed the others in experimental and comparative conditions. Superior segmentation of grey, white, and cerebrospinal fluid improves clinical judgement and diagnosis. Segmenting such complex brain images is difficult, however the multilevel thresholding-based hybridised WCMFO technique is highly recommended.

Separating pure materials from mixed pixels and measuring material abundances is what hyperspectral unmixing in remotely sensed hyperspectral pictures is all about. The three procedures are laid out in detail in the paper, “Dispersion Index Based Endmember Extraction for Hyperspectral Unmixing.” Hyperspectral data endmembers are counted with the use of subspace identification. The second stage, called endmember extraction, involves the deletion of information. End-member extraction is complicated by all three processes. Many researchers, as reported in articles on endmember extraction, have turned to convex geometry for an answer. In this research, authors offer Dispersion Index based Endmember Extraction (DIEE), an endmember extraction method based on convex geometry. The state-of-the-art algorithms are used to evaluate DIEE on both real-world and simulated data. The proposed method works well on both the actual dataset and the noisy simulated dataset.

The authors of the paper “Robust Passive Fault Tolerant Control for Air Fuel Ratio Control of Internal Combustion Gas Engine for Sensor and Actuator Faults” offer a new Passive Fault Tolerant control System(PFTCS) for the Internal Combustion (IC) petrol engine's Air Fuel Ratio (AFR) management system. A fuel throttle valve in the engine's fuel line and a large-feedback Proportional plus Integral (PI) controller govern air-fuel ratio (AFR). Eliminating Analytical Redundancy (AR) simplifies the controller. Hardware redundancy in sensors and actuator assemblies prevents the system from tripping if several sensors fail. Noisy sensor measurements test the proposed PFTCS. In MATLAB/Simulink simulations, the PFTCS is fault-tolerant in quiet and noisy sensor environments without AFR loss. The recommended controller's stability can be assessed by calculating the closed-loop system's poles. Authors assessed the controller's dependability by obtaining the model's probabilistic reliability function. Comparing it to earlier models shows its advantages.

Next, “Latency and Energy Efficient Bio-Inspired Conic Optimized and Distributed Q Learning for D2D Communication in 5G” explains how advertising can employ 5G communication. 5G could connect billions of things and handle massive data with D2D communication. Optimization and machine learning are best for 5G networks' most crucial and unique aspects. BCO-DLQL reduces 5G D2D transfer time and energy. A Bio-inspired Conic Particle Swarm Optimization model changes position and speed to estimate fitness function depending on transmission power and data loss rate to optimise D2D communication. This improves computers and saves power. After that, the Distributed Latency Managed Q Learning method improves connectivity and latency by two times. SINR function for probability factor while picking related actions and reward function assuming neighbour device and communication range. These two functions improve D2D connectivity by reducing latency and data loss. Finally, the neighbour device and data stream communication range reduce D2D communication data loss and latency. BCO-DLQL saves 7% more energy and 24% less time than state-of-the-art works, according to simulations. Simulations show that the proposed solution outperforms the best in energy efficiency, latency, data loss, and system throughput.

In the next paper, “Acceptance Criteria of Bearings-only Passive Target Tracking Solution” bearing measurements determine target motion parameters (TMP) such range, course, and speed. In simulation mode, true values can determine how near the estimated result is to the genuine solution. TMP's real-world effects are hard to determine. This study examines how real-world TMP acceptance requirements have changed. Detailed mathematical modelling and an unscented Kalman filter (UKF) decide TMP. UKF's state vector covariance matrix shows estimated TMP errors, and its standard deviation is utilised to set an acceptance requirement. Submarine-to-submarine tracking determines scenarios. The Monte-Carlo simulation shows results from low angle on target bow (ATB) conditions. Medium and high ATB instances and passive target tracking from submarine to ship or vice versa can be handled similarly.

The next paper on “State of Charge Estimation of Lithium Batteries in Electric Vehicles using IndRNN” introduces a recurrent neural network-based battery model that accurately and robustly predicts remaining charge. Independently recurrent neural network constructive training under distinct experimental datasets from Lithium Nickel Cobalt Aluminium Oxide battery cells at different ambient temperatures produces the suggested state of charge estimation battery model. The suggested model adequately describes the battery's non-linear behaviour without understanding of its internals. Gated recurrent units and long short-term memory show their efficacy. An independently recurrent neural network outperformed a gated recurrent unit and a long short-term memory in accuracy under different electric vehicle drive cycles, with a root mean square error of 0.7633% and a mean absolute error of 0.6389% for varying temperatures.

In “A New Adaptive Fault Tolerant Framework in the Cloud” authors talk about cloud computing's rapid expansion to make failure resilience mainstream. Literature suggests fault tolerance methods to improve cloud service reliability. Virtual machine(VMs) failures cause cloud service reliability and availability difficulties. Thus, this study introduces cloud-based Threshold-Based Adaptive Fault Tolerance (TBAFT) by combining proactive and reactive methods. This study uses proactive VM migration and replication with reactive retry. Experimental validation compares three benchmark fault tolerance techniques using first fit and least full host selection criteria. CloudSim simulator presents experimental findings of the suggested approach in terms of failure rate, throughput, migration, and execution time.

In the paper, “Performance Study for Vertically Quad Gate Oxide Stacked Junction-less Nanosheet,” the authors focus on the performance of quad gate by adding fourth gate to a tri-gate. They carry out simulation study of vertical Quadgate oxide stacked junction-less Nano-sheet being a most promising device structure with in a Nano scale regime, with the use of oxide, work function, and channel engineering for single, double, and triple fins Nano–sheet. From the reference model of trigate junction-less, the structure is modified with a new design approach having same design parameters.

In this study, titled “Three Ways Chip to Chip Communication via a Single Photonic Structure: A Future Paragon of 3D Photonics to Optical VLSI” it is proposed that chips could communicate in three dimensions using a photonic structure in three dimensions. The structure's purpose can be figured out by how well it absorbs and reflects light. Reflectance is calculated using a photonic bandgap analysis and the plane wave expansion method. Absorption is found using an analytical method. In this article, the input signals had low power levels and potentials that ranged from 0.55 V to 1 V. This is done to keep a nanoelectronic or nanophotonic circuit's chip, LED, photo detector, and waveguide from getting too hot. Based on the results, a silicon-based 3D photonic structure with the right lattice spacing and air hole diameter could be the best way to get three-way communication.

This work on “HHO-based Model Predictive Controller for Combined Voltage and Frequency Control Problem including SMES” models and manages a combined load frequency control (LFC) and automated voltage regulator (AVR) system for a multi-area power system network including thermal, diesel, and solar thermal power plants in each generating region. Superconducting magnetic energy storage protects the LFC loop from rapid active power demand changes. The AVR and LFC loops are improved using Model Predictive Controller (MPC). Controller weights are fine-tuned using Harris Hawks Optimization (HHO). The transient performance indices of the MPC-HHO algorithm are compared to those of traditional MPC, PID, FOPID, fuzzy PID, integral double derivative with derivative filter controller, and Particle Swarm Optimization and Sine Cosine Algorithm-based Model Predictive Controllers. MPC-HHO controllers outperform the others.

In the next paper “A Theoretical and Experimental Study of Injection Pulling in Phase -Locked Optoelectronic Oscillator under Radio Frequency Signal Injection,” authors present their work beginning with the single-loop optoelectronic oscillator (OEO), an analysis of the effects of an RF-injected signal on the phase-locked loop OEO. After obtaining the injection locking equation of the oscillator, a time-domain model of a phase-locked loop OEO under RF signal injection is presented. The OEO's behaviour is discussed assuming it is phase-locked to the reference signal and injection-pulled by an independent RF signal. The frequency response of the spurious outputs caused by RF injection signal is discussed in terms of the injection transfer function. For phase noise analysis, an equivalent dual loop model of phase locked loop OEO under RF signal injection is described. The analysis presented is partially supported by the experimental results presented at the conclusion.

In accordance with the CC-CV charging protocol, the authors of “State of Health Estimation of Lithium-ion Batteries based on the CC-CV Charging Curve and Neural Network” introduce two health indices (HIs) that are less dependent on the charging cycle's start. These two metrics strongly correspond with battery capacity variations over time. The neural network's ability to fit nonlinear curves is employed to relate these indices to battery SOH. Performance analysis shows that the proposed method is consistent and effective, with a maximum estimation error of 2%.

In the following paper “Universal Filter Design Using 45nm FinFET Technology-Based Floating Current Source” a Double Gate (DG) FinFET Floating Current Source (FCS) and universal filter are designed. The designed FinFET-based FCS operates at 0.15V powersupply, the power consumption is of the circuit is 51nW and bandwidth is approx 100MHz. The FinFET 45nm PTM-MG model is used to simulate the FCS-based filter circuit in LTspice. The LM13700 integrated circuit is used to test the filter topology behaviour. The findings are shown. The FinFET-based circuit and its application can be utilised to develop systems with minimal power consumption and chip space.

The next paper, titled “Combined Effects of Multi-User Interference and Correlated Fading on MIMO Interference-Unaware Transceiver” examines the effects of multi-user interference and correlated fading on the interference-unaware transceiver (IUT), which changes the transmitter and receiver without knowing about the interference. They show that for IUT under multi-user interference, receive correlated fading has no influence on the achievable rate, and the achievable rate can increase as broadcast correlated fading correlations increase. Even with transmit-correlated fading, the IURT rate can converge to the interference-free MIMO channel capacity as the number of receive antennas increases.

This work on “Symmetrically Direct Coupled Stacked Broadband Microstrip Antenna” offers directly connected stacked patches to increase impedance bandwidth and decrease cross-polarization. Metallic shorting posts (vias) between metallic patches directly excite the top-stack multi-resonator arrangements. Stack directly linked MSA has 25.8% bandwidth, 8.8 dBi gain, and 0.2 dB gain fluctuation over the band. This arrangement has cross-polar values below -15 dB at lower frequencies and -5 dB at higher frequencies. Stacking MSAs with symmetrical direct coupling suppresses cross-polar components. This arrangement has 26.1% bandwidth, 9.3 dBi gain, and ±0.3 dB bandwidth variation. Cross-polar values are reduced by -25 dB at lower frequencies and -16 dB at higher frequencies. The antenna configurations proposed are designed and fabricated. The experimental and simulated outcomes are consistent.

“A Fault-Tolerance Nanoscale Design for Binary-to-Gray Converter based on QCA” shows that the extremely large-scale integration sector has aggressively sought miniaturisation. This nanoscale function raises challenges of size, switching speed, power, and error handling. Quantum-dot cellular automata (QCA) transition quickly and tolerate errors well. Thus, fault-tolerant logic intrigues many QCA researchers. A binary-to-gray converter converts binary data to grey. This simplifies electronic communication errors. This work builds a fault-tolerant binary-to-gray converter in QCA using the majority gate, inverter gate, and wire-based cell redundancy. Using QCADesigner 2.0.3, authors tested the proposed circuits. Their study examined cell loss, migration, misalignment, and duplication using modelling software. Even with one layout mistake, the fault-tolerant two-bit, three-bit, and four-bit binary-to-gray converter can achieve 100% fault tolerance.

Authors in the next paper “Frequency Selective Meta-structure Embedded Two-Element MIMO Antenna with Enhanced Isolation and Pattern Diversity for WLAN/WiMAX Applications” present a two-element MIMO antenna with better isolation and pattern diversity. Dual-band Multiple-Input Multiple-Output (MIMO) technology covers the 5.2 GHz wireless local area network spectrum and the 5.8 GHz WiMAX band. Modifying the angle between the non-parallel sides of a trapezoidal patch supplied by a coplanar waveguide (CPW) produces the MIMO's unit radiator's resonant modes. A frequency-selective meta-structure between the radiating elements reduces reciprocal coupling and creates a diversified pattern. The MIMO system's maximum gain is 1.56 dB at 5.2 GHz (5.1 to 5.34 GHz) and 5.16 dB at 5.8 GHz (5.68 to 5.9 GHz). Port-isolation is 26 dB in WLAN and 23 dB in WiMAX. Channel capacity loss (CCL 0.03) and correlation co-efficient (ECC 9.99) meet MIMO operation standards. Experiments match model predictions.

Authors in their paper “Design of a Low-profile Chipless RFID Tag using a Grounded Wall” suggest utilising a small RFID Tag without a chip for the purpose of identification. In RFID systems, it's crucial that the tags be as small as possible. The original RFID tags featured eight octagonal rings. The tag is split in half horizontally to save space. Remove one substrate component. To protect the remaining portion from the effects of the removed one, a grounded wall is constructed in front of it. We can infer that the smaller tag has a similar RCS reaction after comparing the compact structure's RCS to that of the standard structure. The RFID tag's analogue circuit is similar to the model's full-wave output. The technology can cut the size of a construction in half.

In order to meet the needs of Long-Term Evolution (LTE) applications, this paper on “A Compact Diplexer Using Coupled π-CRLH Zeroth Resonators” presents a novel diplexer configuration that makes use of a newly-coupled composite right/left-handed (CRLH) resonator. Using connected zeroth order -CRLH resonators allows for a significant reduction in the diplexer's footprint because they have zero electrical length. The filters are designed to achieve a desired frequency bandwidth of 4% ∼16.7 Q-factor and ∼0.066 coupling coefficient at a center frequency of 2.1 and 2.6 GHz with transmission zeros. Diplexer rejection is 15–20 dB, with 1 dB of insertion loss maintained for both the transmit and receive bands. Equivalent circuit simulations, full electromagnetic simulations, and experimental measurements are used to validate circuit design assumptions. The observed and simulated results are highly consistent, with a small size of 30x 60 mm ².

An RF Self Optimization Tool (SOT) architecture for a 4G/5G network is presented in this paper titled, “An Efficient RF Self Optimization Tool (SOT) for 4G/5G Mobile Communication”. In particular, an optimisation framework is developed that accounts for several processes, including data gathering from various sources, KPI description, and the optimisation procedure itself. It simplifies monitoring and responding to 4G and 5G network health by highlighting automatic steps that may be done to address performance issues. The proposed strategy is implemented, and its efficacy is evaluated. This demonstrates the automatic identification of a cell with subpar coverage and the identification of means to improve that cell's coverage to the point where it satisfies QoS requirements.

The paper titled “Design of Hybrid Neural Controller for Nonlinear MIMO System based on NARMA-L2 Model” shows how to use rough models and a multilayer perceptron neural network to make a nonlinear adaptive controller for uncharacterized nonlinear dynamical systems. This study combines the MLP and NARMA-L2 models to make a hybrid neural structure that can work as both an identifier model and a nonlinear controller for MIMO nonlinear systems. The best thing about the suggested control system is that it doesn't need model information. Authors use both input and output data to figure out the control input. The NARMA-L2 neural network model weights are fine-tuned by the back propagation optimizer method. The NARMA-L2 neural network controller handles the attitude of the UAV based on the inputs and outputs of a nonlinear model. The suggested controller is made by putting the generalised sub-models in the right order after accurate and efficient system modelling. The behaviour of the controller is modelled by a nonlinear and dynamic quadcopter MIMO system. The results show that the NARMA-L2 neural network did a good job of both modelling and controlling.

Finally, the concluding paper, titled “Pareto Optimal Design of a Fuzzy Adaptive Hierarchical Sliding-mode Controller for an X-Z Inverted Pendulum System” uses Multi-Objective Genetic Algorithm (MOGA) to find the best Fuzzy Adaptive Hierarchical Sliding-Mode Controller (FAHSMC) for the X-Z inverted pendulum system. In a five-step process called “forward transformation,” the system's original state variables are changed into the goal state variables. Control applications require rearranging the X-Z inverted pendulum system's dynamic equations. Then, Lyapunov stability theory shows the controller's stability with the new state variables. A six-stage inverse transformation determines the X-Z inverted pendulum's state and control variables. Finally, the MOGA constructs a Pareto-optimal control mechanism for the X-Z inverted pendulum system. The three inconsistent objective functions for multi-objective optimisation are the X-direction tracking error, Z-direction tracking error, and pendulum angular error. Numerical and graphical findings show that the offered methods generate Pareto optimum fronts better than HSMC and AHSMC.

Additional information

Notes on contributors

Ranjan K Mallik

Ranjan K Mallik (FIETE, FIEEE, FIET, FTWAS, FNAE, FNA, FNASc, FASc) is an Institute chair professor in the Department of Electrical Engineering, Indian Institute of Technology (IIT) Delhi. He received the BTech degree from IIT Kanpur and the MS and PhD degrees from the University of Southern California, Los Angeles, all in electrical engineering. He has worked as a scientist in the Defence Electronics Research Laboratory, Hyderabad, India, and as a faculty member in IIT Kharagpur and IIT Guwahati. His research interests are in diversity combining and channel modelling for wireless communications, space-time systems, cooperative communications, multiple-access systems, power line communications, molecular communications, difference equations, and linear algebra. He is a recipient of the Shanti Swarup Bhatnagar Prize, the Hari Om Ashram Preriot Dr Vikram Sarabhai Research Award, the Khosla National Award, the IETE Ram Lal Wadhwa Award, the IEI-IEEE Award for Engineering Excellence and the J C Bose Fellowship. He is a member of Eta Kappa Nu and a Fellow of IEEE, the Indian National Academies INAE, INSA, NASI, and IASc, TWAS, the West Bengal Academy of Science and Technology, IET (UK), IETE (India), The Institution of Engineers (India) and the Asia-Pacific Artificial Intelligence Association. He served as an Area Editor and an Editor for the IEEE Transactions on Wireless Communications, and as an Editor for the IEEE Transactions on Communications. He was a Technical Program Committee (TPC) Co-Chair for the Wireless Communications Symposium of IEEE GLOBECOM 2008 and IEEE ICC 2010, a TPC Co-Chair for the PHY Track of IEEE WCNC 2013, and a TPC Co-Chair for the Communication Theory Symposium of IEEE ICC 2021. He is currently Deputy Editor-in-Chief of IETE Journal of Research. Email: [email protected]

Shiban K Koul

Shiban K Koulis currently an emeritus professor at the Indian Institute of Technology, Delhi. He served as deputy director (Strategy and Planning) at IIT Delhi from 2012 to 2016 and mentor deputy director (Strategy & Planning, International Affairs) at IIT Jammu from 2018 to 2021. He also served as the chairman of Astra Microwave Products Limited, Hyderabad from 2009 to 2019 and Dr R P Shenoy Astra Microwave chair professor at IIT Delhi from 2014 to 2019. His research interests include RF MEMS, high frequency wireless communication, microwave engineering, microwave passive and active circuits, device modelling, millimetre and sub-millimetre wave IC design, body area networks, flexible and wearable electronics, medical applications of sub-terahertz waves and reconfigurable microwave circuits including miniaturized antennas. He successfully completed 38 major sponsored projects, 52 consultancy projects and 61 technology development projects. He has authored/co-authored 601 research papers, 22 state-of-the art books, 4 book chapters and 2 e-books. He holds 26 patents, 6 copyrights and one trademark. He has guided 30 PhD thesis and more than 100 Master’s theses. He is a Life Fellow of IEEE and Fellow of INAE and IETE. He is the chief editor of IETE Journal of Research, associate editor of the International Journal of Microwave and Wireless Technologies, Cambridge University Press. He served as a Distinguished Microwave Lecturer of IEEE MTT-S for the period 2012-2014.

Recipient of numerous awards including IEEE MTT Society Distinguished Educator Award (2014); Teaching Excellence Award (2012) from IIT Delhi; Indian National Science Academy (INSA) Young Scientist Award (1986); Top Invention Award (1991) of the National Research Development Council for his contributions to the indigenous development of ferrite phase shifter technology; VASVIK Award (1994) for the development of Ka- band components and phase shifters; Ram Lal Wadhwa Gold Medal (1995) from the Institution of Electronics and Communication Engineers (IETE); Academic Excellence Award (1998) from Indian Government for his pioneering contributions to phase control modules for Rajendra Radar, Shri Om Prakash Bhasin Award (2009) in the field of Electronics and Information Technology, VASVIK Award (2012) for the contributions made to the area of Information, Communication Technology (ICT) and M N Saha Memorial Award (2013) from IETE. His name has recently figured in the Scopus Elsevier top 2% Scientists under the Category “Year 2021”. Email: [email protected]

Arun Kumar

Arun Kumar is with the Centre for Applied Research in Electronics, Indian Institute of Technology, Delhi, since 1997. He became professor in 2008 and has served as head of Centre for more than 7 years. He obtained the BTech, MTech, and PhD degrees from Indian Institute of Technology Kanpur in 1988, 1990 and 1995, respectively. He was visiting research rate the University of California, Santa Barbara, USA from 1994 to 1996 before joining IIT Delhi. His research interests are in digital signal processing, under water and air acoustics, human and machine speech communication, and multi-sensor data fusion. Professor Arun Kumar is an inventor on 10 granted US patents. He has guided 16 PhD theses and 180 Master’s theses. He has authored/co-authored 160 papers in peer reviewed journals and conferences. He has been project investigator/co-investigator for 72 funded R&D projects from industry and government. These projects have led to several technology and know-how transfers. Many of the technologies co-developed by him are deployed in the field and are in practical use. Professor Arun Kumar has served on several technical and organization committees of conferences, and on national level committees in electronics and defence fields. He is co-founder and director of a company that develop signal processing and AI based technologies and products for speech-based and multi-modal human and machine. He is currently Deputy Editor-in-Chief of IETE Journal of Research. Email: [email protected]