The current issue of the IETE Journal of Research, Volume 70, Number 2, February 2024) consists of a total of eighty articles. The articles below, grouped by topic, present new developments and ongoing research in the fields of communications (10), electromagnetics (9), computers and computing (25), control engineering (12), electronic circuits, devices and components (7), instrumentation and measurement (4), medical electronics (1), and power electronics (12).
This issue contains ten (10) papers in the field of communications. The first paper titled “A Non-Linear Improved CNN Equaliser with Batch Gradient Descent in 5G Wireless Optical Communication” introduces an improved equalisation scheme that utilises convolutional neural networks (CNN) in generalised frequency division multiplexing (GFDM) for propagation in a hybrid microwave-optical system. The proposed method can address non-linear distortion issues and enhances equalization performance. In the next paper “A Novel Approach for Enhanced Network Formation in 6TiSCH-based IoT Low-Power and Lossy Networks” the 6TiSCH-MC's bootstrapping issue is addressed using two Minimal Cells with Dynamic Channel Offset (TMDC). The TMDC raises the minimum cell count to two and lets parent and kid nodes send and receive control messages while staying in sync with each other. It is brought out that when networks are first set up, the TMDC does it faster, uses less energy, and connects more nodes than the 6TiSCH-MC. The following paper titled “Analysis and Design of Compressive Pulsed Radar Based on Adaptive Pipelined Algorithm” presents an examination of the adaptive CAMP algorithm for pulsed radar signals, focusing on the adaptive CAMP threshold. The performance of the adaptive CAMP algorithm is evaluated by comparing it to the classic approach in terms of detection performance using Receiver Operating Characteristic (ROC) curves, range resolution, and the potential number of detected targets. The next work on “Ball Bearing Fault Classification Using Comparative Analysis of Wavelet Coefficient Based on Entropy Measurement” presents a method for classification of ball bearing faults from accelerometer recordings with wavelet coefficients and an analysis of entropy. The 3rd level decomposition of the residue signal is created for this purpose by eliminating the highest frequency component from the raw signal. The results and comparisons presented bring out the efficacy of classifying ball bearing faults. The authors of the next paper titled “Different Power Adaptive Transmission Schemes over Alternate Rician Shadowed Fading Channels” present closed form expression for determining the capacity of Alternate Rician Shadowed (ARS) fading channels. Different adaptive transmission strategies are studied, such as optimal rate adaptation, truncated channel inversion with fixed-rate, and channel inversion with fixed-rate. Monte Carlo simulation results are presented with different performance metrics. The article “Differential Spatial Modulation with Lattice Reduction Aided Pre-coding” is about a lattice-reduction (LR) aided pre-coding scheme in differential spatial modulation (DSM) systems. A rough upper bound on the average bit error rate (BER) is found using semi-analytic methods. Analytic approach is used to show full diversity gain can be achieved. The performance analysis supported by simulation study shows that the precoding scheme with NT transmit antennas and NR receive antennas can achieve the maximum transmit diversity. “Efficient Distance and Connectivity Based Traffic Density Stable Routing Protocol for Vehicular Ad Hoc Networks” is the title of the next paper in which authors present a Traffic Density Stable Routing Protocol based on Connection- and Distance (TDSRP-DC) to prevent data packet collisions at intersections and an adaptive routing schedule that changes based on the selection at any given time. Various parameters for the optimal path estimation are considered including node distance, node speed, node azimuth, link stability, and link reliability. Results of performance are compared with existing algorithms for complex traffic flow. The authors in the next article “IoT Based Remote Diagnosis and Therapeutic Telemedicine Governing System” delve into the state-of-the-art research and paradigm shifts in the field of remote tele-medicine, discussing how these including IoT will shape the future of assisted living. The authors provide a resource for remote telemedicine through their recently developed technology, the IoT remote diagnostic and therapeutic telemedicine system, which enables patients to get virtual therapy. The next article titled “Performance Improvement of Bistatic Baseline Detection” presents a deconvolved MUSIC (D-MUSIC) algorithm for direction of arrival (DoA) estimation in bistatic scenarios where the desired target echo is immersed in the direct signal. The deconvolution of MUSIC beam power is performed using the point scattering function. It is brought out that the algorithm can improve the MUSIC algorithm's DOA estimation performance at low SNRs by lowering the high background level of MUSIC beam power. The following paper titled “SOSO: Symbiotic Organisms Search Optimization based Faster RCNN for Secure Data Storage in Cloud” presents a Symbiotic Organisms Search Algorithm (SOSA) that uses a faster region-based convolutional neural network (FRCNN) to detect intrusion attacks and classify data types. An Optimal homomorphic encryption (OHE) method is given to keep data safe in the cloud, depending on the type of data. Also, an Elastic Collision Seeker Optimization Algorithm (ECSOA) is given for secure data access by the owner. The proposed model is tested using two datasets and compared with other techniques to make inferences about its efficacy.
From the aforementioned sequence of areas, this issue contains nine (9) articles pertaining to the broad field of electromagnetics. The first paper of this category is titled “A Christmas Tree-shaped Quadband Compact Antenna with Triple Slots for Various Wireless Technologies”. A compact triangular patch supplied with compact coplanar waveguide (CPW) on a FR4 epoxy is presented for quadband applications. The introduction of openings of varying lengths into the patch induces the antenna to resonate at lower frequency bands. The antenna is capable of operating in the different application bands, with different bandwidths as shown by simulation and measurement results. The second paper in this area, titled “Compact, Broadband and High Gain Uniplanar Quasi-Yagi Microstrip Antenna for End-Fire Radiation” is about the design of a compact, broadband, uniplanar, high-gain quasi-Yagi microstrip antenna for end-fire radiation. Combining microstrip and Yagi-Uda antennas lowers inter-element spacing and boom length antenna dimensions. U-shaped reflectors reduce antenna side length. Reflectors and directors improve the antenna's lower- and upper-frequency directivity. The Figure of Merit (FoM) is compared with the reported design. The suggested uniplanar quasi-Yagi antenna is appropriate for 2G, 3G, 4G, Wi-Fi, and portable direction-finding devices that require end-fire radiation. The next paper “Design and Experimental Analysis of Dual Port Antenna with High Isolation for 5G Sub 6 GHz: n77/n78/n79 and WiFi-5 Bands Applications” describes the development of an arc-shaped dual-port MIMO antenna with improved isolation. The antenna provides improved isolation from 3.28 to 5.93 GHz without a matching network, neutralisation line, or decoupling structure. The designed MIMO model is expected to be suitable for 5G sub 6 GHz wireless services because of its improved isolation, reflection coefficient, efficiency, and peak gain. The following work titled “Design and Mode Matching Analysis of Stepped Substrate Integrated Waveguide and Filters” presents the design and fabrication of a stepped substrate integrated waveguide. The scattering parameters are determined by mode matching analysis. The mode matching methodology is compared with the HFSS finite element method and CST-MWS finite integration method in terms of processor computation time, memory use, reflection, and transmission properties. The developed stepped substrate integrated waveguide exhibits band pass filter properties well-suited for applications in the X-band, Ku- band, as well as K-band applications. The paper titled “High Gain Passive UHF RFID Reader Antenna using Novel FSS for Longer Read Range” discusses a Frequency Selective Surface (FSS) and miniaturised passive UHF RFID reader antenna that is designed, analysed, and fabricated. The global Ultra-High Frequency reader antenna is useful for wireless RFID applications. The Fabry-Perot arrangement of FSS sheet over the antenna boosts radiating gain without changing antenna profile or radiation patch size. The integration of the proposed FSS with passive UHF RFID antenna is expected to enhance read range, gain, power consumption, and immunity within the resonant band in wireless RFID applications. Next, the paper “Investigations on the Wideband Characteristics of a Cylindrical Conformal U-slot loaded Microstrip Patch Antenna for X Band Airborne Applications” presents design and investigates a wideband U-slot-loaded cylindrical conformal antenna for X band usage. Analyses were done for both axial and circumferential antenna orientations on the cylindrical conformal surface. Wideband U slot designs for planar surfaces have been analyzed and algorithms developed. In the paper titled “Ku-Band SIW Filter with High Fractional Bandwidth Optimised Using Feed Forward Back Propagation ANN”, the authors investigate an artificial neural network (ANN) based miniaturised wideband substrate integrated waveguide (SIW) filter. The measured return-loss and insertion loss within the pass-band are presented. The filter characteristics in terms of passband, size, insertion loss, return loss make it suitable for Ku-band satellite communication. It is observed that the time taken by the ANN is much less than that taken by CST software. The approach presented is a suitable optimisation technique in the design of RF and microwave components. The paper titled “Miniaturised Vivaldi Tapered Slot Antenna (VTSA) with Microstrip to SIW feed Structure for X Band Application” presents the simulation study and fabrication results of a basic antenna element designed for use in the X band. The operating frequency range of the structure is between 8 to 12 GHz (X band). This band has potential uses in radar, imaging, medical, space communication, and military applications. Further enhancements through the implementation of an array, will be suitable for various applications including wall penetration, medical imaging, and radar. The next paper titled “Rapid Fault Detection with Periodic Update Feature for Transmission Line Parameters in HVDC Grids” presents a fault detection approach that utilises local measurement data and the characteristics of incoming fault Travelling Waves (TW) to detect faults based on rise time. The dominant frequency of the primary wavefront is determined by the rise time of the incoming fault TW. The problem location is detected by utilizing auto-updating transmission line data and the dominant frequency of the incoming travelling wave.
This issue has twenty-five (25) papers that span many aspects of computers and computing. In the first manuscript, titled “A Deep Belief Network Model for Automatic Atrial Fibrillation Detection”, a Chimp Optimization algorithm-based parameter optimized Deep Belief classifier model is presented for the detection of atrial fibrillation. Its lower computational complexity, reliability and classification accuracy results are discussed. The next paper titled “A Deep Learning Approach based on Faster R-CNN for Automatic Detection and Classification of Teeth in Orthopantomogram Radiography Images” presents a model based on Convolutional Neural Network (CNN) to detect and classify teeth and anomalies. The categorization process is based on Orthopantomogram radiographic images and it categorizes teeth into four classes and abnormalities into two classes. The next paper titled “A Framework of Intelligent Mental Health Monitoring in Smart Cities and Societies” aims to tackle the issue of preventing mental health disorders by early stage prediction using the web portal “Mind Turner”. The method uses random forest classifier to detect stress levels using question-answer-based assessment, SVM based facial emotions detection and fuzzy logic to classify probable mental health state of an individual into one of three classes. The next paper titled “A Heuristic Neural Network Approach for Underwater Parametric Prediction at Bay of Bengal” presents a method for enhanced accuracy in predicting ocean properties such as temperature, pressure, salinity, and density. The method uses heuristic neural network (HNN), long-short term memory (LSTM) and repeated iterative technique (RIT). The paper discusses results of prediction accuracy obtained. In the paper titled “A New Approximate (8;2) Compressor for Image Processing Applications” the second stage of the multiplier circuit (i.e. reduction of partial products) for image processing applications is investigated. By designing an approximate (8;2) compressor, the circuit design overhead is reduced. The approximate multiplier is compared with other available approximate compressors in terms of quality, power consumption, delay and area in the circuit. Next, the paper on “A Novel Back-Propagation Neural Network for Intelligent Cyber Physical Systems for Wireless Communications” discusses how cyber physical systems (CPS) may improve real-world-virtual communication. Different CPS-based indoor design plans incorporate measurement in smart buildings. The control system which include modules for detection, tracking, execution, and communication may use neural networks and data fusion tools. Granular formal principles underpin the CPS information world, and granular computing theory has been researched. The paper titled “A Stochastic Model for Performance Evaluation of Hybrid Network Architectures of IoT with an Improved Design” presents an analysis of hybrid network architectures for IoT communications. A hybrid network is presented that aims to optimize the advantages of both wired and wireless networks. To assess the dependability of different hybrid network designs, a Markov based stochastic model is presented. The analytical results obtained from Continuous Time Markov Chains (CTMC) are discussed. Different performance parameters are presented for the efficacy of hybrid networks. The next paper titled “A Survey of Machine Learning Applications in Renewable Energy Sources” discusses how machine learning can be used in renewable energy sources. These machine learning methods are mostly used to predict how much power will come from clean energy sources like solar, wind, water, biomass, tide, and geothermal. The paper also discusses how machine learning can be used to predict faults before they happen, find faults early, and figure out issues with green energy systems. The article titled “A Unified Neuro-Fuzzy Framework to Assess the User Credibility on Twitter” presents a unified approach for evaluating user credibility on Twitter. This is achieved by analyzing three fundamental credibility-related factors derived from ecommerce and social media platforms: the likelihood of being a promoter, a spam bot, and/or a spammer. In order to determine the credibility of a Tweeter, the factors are estimated utilizing a deep learning baseline model and/or further analyzed utilizing a fuzzy inference system. The results of the proposed method are presented. The next paper on “An Advanced Circular Adaptive Search Butterfly Optimisation Algorithm for CNN Based Sleep Apnea Detection Approach” describes the development of an automated system for detecting sleep apnea from pulse photoplethysmography (PPG) signals. The proposed method enhances the accuracy of classification by implementing a refined classifier and feature extraction method. Hilbert Huang Transform (HHT) with extrema selection reformed (ESR) Empirical mode decomposition (EMD) is presented as a feature extraction method in this paper. Conducting an investigation into various scenarios, the research paper titled “An Investigation of the Optimum Power Allocation Technique in MIMO-NOMA Network with Deep Limited Search Algorithm” determines an efficient method for allocating power to users in Multi-input multi-output Non-orthogonal multiple-access (MIMO-NOMA) communication networks whose signals are feeble. The studies include multi-user-optimal power allocation (OPA) with Depth Limited Search Algorithm (DLSA) and Deep Neural Network (DNN), multi-user-OPA, and two-user-OPA. In both two- and multi-user instances, power distribution decreases with user count. Power distribution in multiuser-OPA is seen as more efficient when DNN is utilized with DLSA. Inferences are drawn from the scenarios studied. In “Attack-Detection and -Recovery: An Integrated Approach towards Attack-tolerant Cyber-Physical Digital Microfluidic Biochips,” authors explain that a Digital Micro-Fluidic Biochip (DMFB) with cyber-physical adaptation implements complex bio-protocols with high precision and high throughput for safety-critical applications like point-of-care diagnosis, personalized medicine, and drug development. This paper proposes an attack-tolerant synthesis with two-way security by incorporating attack detection and recovery from DoS attacks. A selective re-synthesis method allows the biochip to perform numerous recovery processes simultaneously. The system adapts to attacks since the recovery technique and detection procedure are linked. Different benchmarks are used to show the efficacy of the two-way attack-tolerance technique. In the next paper, “Automated Breast Boundary Segmentation to Improve the Accuracy of Identifying Abnormalities in Breast Thermograms,” the authors propose a Distance-based Metrics and High-Temperature Region-based Adaptive Thresholding (DM-HTRAT) method for segmenting and dissecting left and right breasts. The proposed approach has comparatively high accuracy. It is surmised that segment breast thermal images and detect breast anomalies reliably and effectively. In “Automated Spam Detection using Sandpiper Optimisation Algorithm based Feature Selection with Machine Learning Model,” authors provide an Automated Spam Detection using Sandpiper Optimization Algorithm based Feature Selection with Machine Learning (ASD-SPOFSML) model. The ASD-SPOFSML method uses feature selection and classification to detect and categorise spam. Improved Mini Batch K-Means Normalised Mutual Information is used for feature extraction in ASD-SPOFSML, while Fire Hawk Optimizer (FHO) algorithm optimizes centroid selection. Sandpiper optimisation (SPO) technique decreases training complexity and improves classification accuracy. Also, Radial Bias Neural Network (RBNN) classifier is used to detect email spam. Different models are compared with the enhancements obtained from ASD-SPOFSML. The authors of the paper “Blockchain based Light-weight Authentication Approach for Multiple Wireless Sensor Network” suggest a method for verifying multiple wireless sensor networks using public blockchain and Light-Weight Authentication Algorithm (LWAA). This method is designed to improve the security and performance of authentication in the IoT environment. The evaluated performance encompasses total power consumption, throughput, latency, packet delivery ratio and time computation and results are compared with other existing methods. The authors of the paper titled “BTLA-LSDG: Blockchain-Based Triune Layered Architecture for Authenticated Subgraph Query Search in Large-Scale Dynamic Graphs” discuss the problems of scalability, security, and inadequate indexing in subgraph mining in a large collection of graph database. To resolve related issues, a proposed solution called BTLA-LSDG incorporating a Four-Q-Curve method is proposed for authenticating data owners and users. It proposes method for Feature sets computation for given query, method for reduction of subgraphs and RNN based subgraph isomorphic testing. The following paper titled “Deep Learning-based Prioritised Packet Classification and Optimal Route Selection in Wireless Multimedia Sensor Networks” presents a method for prioritizing packet classification in wireless multimedia sensor networks. This method utilizes a word embedding mechanism to extract packet semantics and employs Long Short-Term Memory model to classify packets based on their header characteristics and to determine their priority. Additionally, the paper introduces a hybrid meta-heuristic algorithm called Butterfly-based Rider Optimisation Algorithm (B-ROA), which takes into account packet priority and other characteristics when selecting the route. In “Effective Epileptic Seizure Detection using Enhanced Salp Swarm Algorithm based Long Short-Term Memory Network,” a Salp Swarm Algorithm (SSA) based LSTM network is implemented to improve epileptic seizure detection. Features are selected and classified with the SSA-LSTM network. In this work, the modified SSA model is used to select discriminative features, reducing system complexity and the curse of dimensionality. The SSA LSTM classifier is tested on standard datasets to establish its efficacy. The paper “Generative Adversarial Networks Classifier Optimised with Water Strider Algorithm for Fake Tweets Detection” presents an algorithm for fake tweets identification. Twitter features are picked using Bag of Words (BOW) model, mutual information approach, and Chi-square method. Selected tweet features are trained with Waiter Strider optimization algorithm (WSOA) on Generative Adversarial Networks classifier. The efficacy of the classifier in separating actual and false tweets is presented. The paper, titled “Hand Anatomy and Neural Network-Based Recognition for Sign Language” proposes a model for the recognition of sign language using neural networks. The method utilizes a combination of computer vision techniques for essential hand landmarks selection, and neural networks to accurately identify sign language gestures. The approach is assessed using a composite set of everyday gestures in sign language. In the paper titled “Human Age Estimation Using Deep Convolutional Neural Network Based on Dental Images (Orthopantomogram)” the authors create a convolutional neural network (CNN) classifier for age classification using orthopantomogram (dental images). The third molar teeth serves as the basis for the technique. CNN classification models including ResNet and Sequential are studied. The paper presents results to show the accuracy of the method. The article “Improving Coverage and Vulnerability Detection in Smart Contract Testing Using Self-Adaptive Learning GA” presents an approach called the self-adaptive learning Genetic Algorithm (self-adaptive learning GA) developed to tackle different challenges that arise during the automatic generation of test cases for smart contracts. The research work demonstrates benefits over current approaches for test case generation by offering a resolution method for bolstering the security of smart contracts and ensuring their robustness within the decentralized finance (DeFi) ecosystem. A machine learning method is proposed in the next paper “Leung-Malik Features and Adaboost perform Classification of Alzheimer’s Disease Stages” to extract features from filtered structural MRI images of people with Alzheimer's disease (AD), mild cognitive impairment (MCI), and Cognitive Normal (CN). The accuracy with Adaboost and Leung-Malik (LM) features at distinguishing AD-CN, AD and MCI, and at sorting multiple classes is presented. Advantages over other methods such as issues of data leaks and bias are discussed. The next paper on “Ontology-Assisted and Autonomic Testing Verified Model for Automated and Reliable Web Development” presents a web engineering framework based on three fundamental phenomena: structured development, high reliability, and multi-level flexibility. By forming and mapping the ontology, a structured, user-assisted design is produced. This model incorporates the user requirements by utilising an ontology map. The effectiveness and dependability of the proposed model in the areas of template support, requirement gathering, customization, control validation, testing, and security are determined by the analytical study. The authors in their article titled “Visual Cryptography Secret Share Creation Techniques with Multiple Image Encryption and Decryption using Elliptic Curve Cryptography” employ visual cryptography and elliptic curve cryptography (ECC) for covert image share creation method. Public key cryptography generators do the encryption process, and secret key arbitrarily generators of the ECC method perform the decryption process. The paper presents comparisons in terms of image quality, errors and image security.
There are twelve (12) articles on control engineering in this issue. The paper titled “2-DOF Preview Feedforward Sliding Mode Controller for the Control of Multivariable Process with Dead Time” presents a two-degrees of freedom (2-DOF) preview feedforward sliding mode controller (PFFSMC) algorithm that utilises a combination of feedback and feedforward terms in the sliding surface. The controller is designed to effectively regulate a multivariable process with dead time, achieving both set point tracking and disturbance rejection. The proposed controller is utilised to control a Wood and Berry binary distillation column, which consists of top and bottom products with certain compositions. The 2-DOF PFFSMC is compared with existing controllers in terms of settling time and percentage overshoot. Additionally, its robustness against ±5% parametric uncertainties in gain, time constant, and dead time is presented. The paper titled “A Behavioural Study of Different Controllers and Algorithms in Real-time Applications” focuses on examining the behaviour of different controllers and algorithms in practical applications. It includes a comparative analysis of the response of a magnetic levitation system with different controllers and algorithms. The paper aims to evaluate the performance of magnetic levitation systems using a Proportional Integral Derivative controller based on the Particle Swarm Optimization algorithm. The authors of the paper, titled “A New Model Reduction Technique for the Simplification and Controller Design of Large Scale Systems” introduce an approach for simplifying and designing controllers for large-scale linear dynamical systems. This approach works well for both large-scale single input single output (SISO) and multiple input multiple output (MIMO) models. The approach maintains the stability of the lower order plant, as long as the higher order system (HOS) is stable. The proposed strategy guarantees the retention of stability and static characteristics of the higher order plant in the reduced model. To verify the accuracy as well as effectiveness of the suggested method, it is applied to standard real-time systems. In the paper titled “Adaptive Neuro Fuzzy Inference System based Bass-Gura Controller for Solar Powered SEPIC Converter” the performance of a solar-powered reduced order SEPIC converter is evaluated by implementing closed-loop control with both a Bass Gura controller and an ANFIS-based Bass Gura controller. The Moment Matching Method is employed to reduce computational time and the number of sensors. In comparison to the Bass Gura controller, the ANFIS-based controller reaches the target set point value for temperature and radiation fluctuations with a shorter settling time. Other aspects of the ANFIS-based Bass Gura controller are also presented. The next paper titled “Design and Development of a Low-cost Vision-based 6 DoF Assistive Feeding Robot for the Aged and Specially-abled People” introduces a cost-effective and indigenous 3D printed 6 degrees of freedom robotic arm. This arm is designed to assist specially-abled individuals and patients with neurological disorders in their feeding process, enabling them to feed themselves independently. In the paper titled “Frequency Control of Electric Vehicles Integrated Isolated Renewable Microgrid using Magnetotactic Bacteria Optimized Cascade Controller,” the authors suggest using a PI-PD secondary frequency controller to enhance the frequency profile and stability of a fully renewable isolated microgrid when there are discrepancies between power generation and demand. In addition, investigations are conducted to determine the most favourable parameters for biogas and biodiesel facilities. The effects of electric vehicles (EVs) are also examined through multiple case studies. The study is useful for creating effective control mechanisms for microgrids in remote locations and for improving multiple frequency frameworks. The authors of the research titled “Improved Dynamic Performance of the Fuel Cell-fed Boost Converter using Super Twisting Sliding Mode Control Strategy” study the super twisting sliding mode control (STSMC) strategies and compare it with the conventional sliding mode control (CSMC) control techniques for fuel cell fed boost converter. A comparison has been made between the performance of both controllers in terms of their ability to handle wide load variation and reference voltage tracking. Simulation and experimental results demonstrate the efficacy of the proposed STSMC in terms of recovery time and voltage overshoot across a wide range of load variations. The paper titled “Inter-harmonics Mitigation for PV based Converters Using INHARE MPPT Algorithm” presents an advanced INter-HARmonic-Elimination (INHARE) algorithm that aims to reduce the fluctuating behaviour of photovoltaic (PV) systems. It is achieved by lowering voltage ripple and settling time. In the case of variable irradiances at constant temperature, the given INHARE algorithm is examined for a 0.52 kW PV system, where the inter-harmonics content is reasonably reduced in the load current. The authors of the paper titled “Nonlinear Robust Adaptive Sliding Mode Control Strategy for Innate Immune Response to Influenza Virus” aim to develop a control strategy that is both nonlinear and robustly adaptable for a mathematical model that describes the innate immune response to infection by the influenza virus. This model is based on the concept of resistance to infection, which is determined by the presence of IFN molecules and the removal of infected cells by natural killer cells. Two control measures, namely vaccination and antiviral treatment, are implemented in order to completely eliminate the virus. The next paper titled “Sliding Mode Control for Wind Turbine Emulator based on Advanced Space Vector Modulation Technique for Two-Phase Induction Motor Drive” proposes the design of a Wind Turbine Emulator (WTE) system that reproduces precise static and dynamic WT features in a lab setting. The TPIM prime mover of the design is fed by a two-phase inverter. The motor is subjected to the SMC approach in order to guarantee optimal speed and flux trajectory tracking. Different parameters, such as electromagnetic torque, rotor fluxes, stator currents, and, rotor speed, are analyzed including static and dynamic characteristics and the WTE transient and steady-state responses. The authors of the paper “Smoothed Functional Algorithm with Norm-limited Update Vector for Identification of Continuous-time Fractional-order Hammerstein Models” propose a smoothed functional algorithm with norm-limited update vector (NL-SFA) to identify continuous-time fractional-order Hammerstein models. Specifically, to address the problem of high tendency of divergence during the identification process, the standard smoothed functional algorithm (SFA) based approach is modified by implementing a limit function in the update vector of the standard SFA based method. The article titled “Static Output Feedback Based DFIG Controller Design for Wind Driven Scheme” discusses the use of Doubly Fed Induction Generator (DFIG) in Wind Energy Conversion Systems (WECS). The paper emphasizes the need for adequate control systems to achieve optimal performance and efficient operation of the DFIG system. The controller design for the DFIG Transfer Function model, uses a Static Output Feedback Technique (SOF). The system's output responses are compared to the Genetic Algorithm (GA) based technique.
The next seven (7) articles in this issue address the subject of electronic circuits, devices and components. The first paper in the category titled “An Advance Method of Testing Memories using Vedic March Algorithm” introduces a novel approach for testing RAMs using Vedic March Algorithm (VMA). The proposed system utilizes a Built-in Self-Test to generate a randomised cyclic address using the Vedic March Algorithm, thereby enhancing the effectiveness of RAM testing. In the next paper titled “A 585.9 µW Complementary VCO with LC Head-and Tail Filtering Achieving 196.7 dBc/Hz FoM” a CMOS voltage control oscillator (VCO) with full and dual second harmonic filtering is reported. Both VCO head and tail LC filters improve oscillator power efficiency. When they resonate at double the oscillation frequency, two high-impedance paths prevent the PMOS and NMOS-gm differential pairs from loading the main LC resonator. The gate-to-source voltage of the two -gm differential pairs is reshaped to reduce phase noise. The 65-nm CMOS VCO achieves a competitive FoM. The authors of the paper “Bio-Inspired Methods for Defect-Tolerant Function-Mapping in Nano-Crossbar Arrays” investigate traditional sorting methods as well as two alternative approaches using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). These methods aim to determine the best assignment of various functions in a nanoscale crossbar circuit that contains defective cross-points. The goal of the proposed approach is to efficiently map a vast number of functions onto a defective-crossbar of significant size, if a solution exists. The number of generations needed to find a solution can vary based on the location of defect points and the inputs of the functions, even if the defect % is the same. The following paper titled “Common Android Smartphones and Apps for Cost Efficient GNSS Data Collection: An Overview,” explores the potential of commercial smartphones and reviews the capabilities of Android apps for cost-efficient GNSS measurements in the geospatial community. It also introduces a novel classification of these apps based on their capabilities and usability. The results of the study demonstrate the modest yet possible solution precision of typical smartphones in real-time location. These findings indicate that smartphones can be effectively utilised in geomatics applications, as well as for improved app development and for IoT-based systems and infrastructure development. The paper titled “Electronically Tunable Current Mode Instrumentation Amplifier employing Single DV-EXCCCII” introduces a novel design for a current mode instrumentation amplifier (CMIA). This design utilises a single differential voltage extra-X current controlled current conveyor (DV-EXCCCII) and a grounded resistor. The proposed instrumentation amplifier circuit has a high output impedance, allowing for easy cascading with other current mode circuits without the need for a buffer. Furthermore, the proposed circuit is electronically tunable with the bias current of the active element used. This circuit provides excellent frequency performance, with a wide range of differential gain and common mode rejection ratio (CMRR) bandwidth. The following paper titled “Fast and Low-Power CMOS and CNFET based Hysteresis Voltage Comparator” introduces hysteresis voltage comparators that are based on CMOS and CNFET technologies. These comparators are specifically designed for low-voltage applications. The given hysteresis voltage comparator circuits have a power-delay-product that is only 0.04-0.32 times that of other hysteresis voltage comparator circuits. Additionally, their execution requires less transistors. The authors of the paper “On Computation and Analysis of Entropy Measures for Metal-Insulator Transition Super Lattice” discuss about the properties of metal-insulator transition Superlattice (GST − SL) and how it can be changed by adding a thin film using femtosecond, picosecond, and nanosecond laser ablation. They then present the numerical bond properties, including degree-based topological indices and their corresponding entropies.
This issue contains four (4) articles that pertain to instrumentation and measurement. The article titled “Design of LQR based FLC for the Optimal Regenerative Braking Controlling of Solar PV based Electric Vehicle System” discusses about how to control an electric vehicle's speed and torque so that it can brake itself using regenerative braking. First, an electric car is modelled and then it is driven in regenerative braking mode. The linear quadratic regulator (LQR) method is used to fix the problems with current methods. Next, a fuzzy logic controller (FLC)-based LQR is used to get the best speed and torque control during regenerative braking in an electric vehicle. The following article “Optimal Parameter Estimation of Solar Photovoltaics through Nature Inspired Metaheuristic and Hybrid Approaches” presents two different ways of estimating the parameters of a solar photovoltaic mathematical model. These are the Pheromone Value Black Widow optimisation (pv-BWO) algorithm and the Hybrid-Sailfish optimisation (h-SFO). The objective function of RMSE is used and the resulting accuracy is compared with other existing methods. The paper “Recognition System for Ergonomic Mattress and Pillow: Design and Fabrication” presents a methodical way to find the right pillows and mattresses to rest and sleep well. A set of force-sensing resistors (FSR), thermal sensors, humidity-thermal sensors, and a central unit to process the data are used in the system. Customised LabVIEW software is made to prepare the method and find the best ergonomic beds and pillows for each user. The next paper is titled “The Velocity of Underwater Ultrasound at Different Temperatures”. In this study, two-step method for measuring the ultrasound velocity underwater at various temperatures was described. The tests were carried out underwater with concentrations as high as 2 M. Authors report that ultrasonic velocity increases at different temperature levels in the experiments. The measurement results showed that the ultrasonic velocity in the used aqueous solutions was significantly different from that in seawater, even when they are at the same temperature and salt concentration. It is inferred that ultrasonic speed measurements can be used to distinguish between chemical components kept at the same temperature.
Only one (1) article in this issue covers the topic of medical electronics. The paper is titled “An Efficient Liver Disease Prediction using Mask-Regional Convolutional Neural Network and Pelican Optimisation Algorithm”. This research presents a modified architecture named Mask-regional Convolutional Neural Network (MRCNN) for the purpose of predicting liver disease. The implementation of the mask RCNN model accurately identifies the location of liver illness in the datasets. Details of loss function, datasets used and discussion of results are presented.
This issue comprises twelve (12) power electronics related research articles. The paper titled “A Critical Review on Hybrid-Topologies, Modulation Techniques, and Controlling Approaches of Modular Multilevel Converter for Grid Integration,” provides an analysis of modular multilevel converter (MMC) with hybrid topological derivatives, modulation strategies, controlling approaches, and their applications in many areas of power system engineering. The paper examines the historical progression of mathematical models used to describe MMC circuit topologies. It addresses both the development and technical challenges associated with classical and model predictive control systems. The potential future directions of MMC applications are also discussed. The paper titled “A High Voltage Gain Multi-Stage DC-DC Boost Converter with Reduced Voltage Stress” presents the design of a transformerless DC-DC boost converter with adjustable gain and non-isolated operation. The converter offers a flexible power supply with several ports, less stress on the switching voltage, and improved efficiency over a wide range. The converter is tested using a 100 W resistive load for which the results are discussed. The following paper titled “A Novel Protection Method to Enhance the Grid-Connected Capability of DFIG Based on Wind Turbines” presents a hybrid method based on the control methods for the RSC, GSC, STATCOM, crowbar, DC-chopper, and SDR to enhance the grid-connected capability of the DFIG-WT system. The rotor side converter (RSC) and grid side converter (GSC) are both controlled by proportional-integral (PI) controllers in the given method. This includes the protection devices: the static compensator (STATCOM), the crowbar, the series dynamic resistor (SDR), and the DC-chopper. The proposed method uses proportional-integral (PI) controllers to control the STATCOM, and it uses the allowable threshold values of rotor current and DC-link voltage to control the other protection devices. The paper titled “An Adaptive Control of Electric Vehicle based on Nine Switches Inverter Fed Two Induction Motors” presents an adaptive control system for two induction motors driven by a Nine Switches Inverter. A Space Vector Pulse Width Modulation (SVPWM) approach is utilized to control the two driving wheels of an electric vehicle using the IFOC technique. This strategy is built on two virtual three-phase inverters. Additionally, an electric differential is incorporated to guarantee the stability of the electric vehicle during turns. The electric powertrain solutions have the potential to decrease the number of electrical and mechanical components, such as power switches and mechanical differentials. An Efficient MPC based Droop Control Strategy for Power Sharing in a Hybrid AC/DC Micro-Grid using Renewable Energy Resources” examines the efficacy of the MPC control method in relation to power sharing via the interlink converter (IC) in a hybrid microgrid that uses both alternating current (ac) and direct current (dc). To guarantee accurate power distribution throughout the microgrid, a droop mechanism based on MPC is employed. To maximise power harvesting from wind and solar systems in the face of changing weather conditions, a MPPT controller based on maximum power conversion efficiency (MPCE) is given. Large quantity of renewable energy is actively supplied to a hybrid microgrid for efficient power management, regardless of variations in sources or loads. The paper “Analysis of Price-Based Demand Response Program Using Load Clustering Approach” groups transformer centre consumers by load profile using K-Medoids. Consumer baseline load (CBL) is estimated using several approaches to determine each consumer's typical consumption behaviour. Forecasts are more accurate, less biased, varied, and dependable using the new ANN-based CBL estimate method. The price demand model shows that elasticity, incentives, engagement, and prices affect DR program enrollment. A given method solves the time of use (TOU) price multi-objective optimization issue. The algorithm optimizes peak load, peak valley difference, and utility benefit. This improves customer satisfaction and the utility's economy. The next article “Design and Analysis of Shunt Active Power Filter with ε-NSRLMMN Adaptive Algorithm for Power Quality Improvement in Distribution System” presents a control method the Shunt Active Power Filter (SAPF) using an adaptive normalised Sign Regression Least Mean Mixed Norm (ε-NSRLMMN) algorithm to compensate for the grid current harmonics and reactive power when the loads are balanced or unbalanced. The adaptive ε-NSRLMMN control algorithm improves power quality and makes the source current sinusoidal and power factor (PF) close to unity. A three-phase distribution network uses it to make up for lost power due to heavy loads. An adaptive method is used to get the basic active component out of the distorted load current. Better stability, less harmonic distortion, less complexity, and less steady state error are some of the benefits discussed about this control method. The paper titled “Design of 15-Level Non-Modular Multilevel-Inverter in a Grid-Connected Solar PV System: A Hybrid ZOA-SNN Technique” presents a novel approach for a 15-level inverter method in a grid-connected photovoltaic (PV) system, using a hybrid strategy. The proposed method, with the acronym ZOASNN, combines the Zebra Optimisation Algorithm (ZOA) with the spiking neural network (SNN). The primary objectives of the ZOASNN strategy are to meet the power requirements of the load, reduce harmonics, and enhance the power regulation and energy conversion efficiency of the PV system. The objective of the paper titled “Optimal Control of BESS for improved Grid Integration of the Hybrid DFIG/PV System using Dual-Layer Adaptive Control,” is to develop a cost-efficient configuration, optimize the design algorithm, and create a comprehensive control system for a grid-connected DFIG-solar and wind-solar hybrid system. The research objective focuses on two main challenges: maximising power extraction from wind and solar energy sources while enhancing efficiency, and improving power quality (PQ) with a dual-layer, variable-step LMS based adaptive management on the demand side (grid and load side). The paper titled “Optimal Locating and Sizing of DG in Radial Distribution System Using Modified Shuffled Frog Leaping Algorithm” presents about how to use a Modified Shuffled Frog Leaping Algorithm (MSFLA) to add distributed generation (DG) to a distribution scheme to increase node voltages and lower power loss in radial distribution systems. It is the main goal to lower the system's active power losses while keeping the voltage profiles within the system's set limits. The paper “PV Charging Station with VSS-IMSAF and SOSMCC Disturbance Observer Based Controls to Enhance the Distribution Grid Capability” describes a three-phase grid-tied (GT) photovoltaic (PV) charging station (CS). By improving power quality, the planned CS will assist the distribution grid accommodate large EV loads. The variable step size improved multiband adaptive structured filter (VSS-IMSAF) technique controls the voltage source converter (VSC). The control can manage grid currents and determine the proper step size to improve CS performance by changing the step size. Electric car battery (EVB) charging and discharging functions are built in to it. The final paper in the issue titled “SOC-Based Fast and Stable Charging Control Using Multilevel DC-DC Buck Converter for EVs,” recommends utilizing a multilevel buck converter to quickly charge an electric car battery and safely. The phases of the converters have been controlled by the state of charge (SOC), which results in an efficient system in the rapid charging region. For 0–20% SOC, charging is recommended at a moderate rate while rapid charging is advised for 20–80% SOC. Slow charging is advised for 80–100% SOC. The method aims to extend battery life. SOC is estimated using Coulomb's counting. A method to achieve this is studied in simulation and is set up to control how the different levels of a three-level-buck converter.
We hope that these articles covered in this issue will provide readers and members of the academic community with valuable insights that they will be able to integrate into their future scholarly endeavours.
Additional information
Notes on contributors
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 researcher at the University of California, Santa Barbara, USA from 1994 to 1996 before joining IIT Delhi. His research interests are in digital signal processing, underwater and air acoustics, human and machine speech communication, and multi-sensor data fusion.
Professor Arun Kumar is an inventor on 11 granted US patents. He has guided 20 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]
Shiban K Koul
Shiban K Koul is 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 615 research papers, 23 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 LalWadhwa Gold Medal (1995) from the Institution of Electronics and Telecommunication 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”. Additionally, Prof Koul has been bestowed the distinguished IETE-Lifetime Achievement Award 2023 by the IETE. Email: [email protected]
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 Prerit Dr Vikram Sarabhai Research Award, the Khosla National Award, the IETE Ram Lal Wadhwa Award, the IEI-IEEE Award for Engineering Excellence, and the JC 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]