The IETE Journal of Research, Volume 70, Number 3, 2024, has 80 papers in its March issue. The articles encompass recent breakthroughs and ongoing research in various fields, covering communications (8), electromagnetics (11), opto-electronics (1), computers and computing (23), control engineering (4), electronic circuits, devices and components (7), instrumentation and measurement (1), medical electronics (4), and power electronics (21).
In accordance with the aforementioned subject areas, this issue contains eight papers on communications. In the first paper titled “A Novel Adaptive Beamforming Technology for Mobile Communication”, the authors employ a speeding unit device to enhance the rate of convergence of the LMS beam-former. The proposed method, referred to as the improved Least Mean Squares (LMS) method, achieves precise adaptive beamforming within 6-7 iterations. To enhance it further, they employ Hanning, Hamming, and Kaiser Windows to reduce the levels of peak side-lobes. Therefore, the suggested approach has the potential to be a viable way for future cellular communications. In the next research titled “An Energy-Efficient Protocol based on Recursive Geographic Forwarding Mechanisms for Improving Routing Performances in WSN,” the authors introduce a Geographic Forwarding Energy Efficient Routing Protocol. This protocol aims to enhance the lifespan and performance of the network. The routing methodology is designed by incorporating many additional phases such as the categorization of nodes according to their energy level, specific criteria for selecting a node as a region head, utilization of multi-hop communication mechanisms, and excluding dead nodes. The authors of the article “Design and Analysis of Sidelobe Reduction Filter For Polyphase Frank Codes” suggest a method for reducing the Peak Sidelobes Level (PSL) of Frank polyphase codes via sidelobe reduction. The optimization of the weights for the Sidelobes Reduction Filter (SRF) is achieved through the implementation of the Modified Genetic Algorithm (MGA). The proposed method substantially reduces the sidelobe level of the autocorrelation peak. The primary objective of the next proposed paper, entitled “Markov Chain-based Mobility Prediction and Relay-node Selection for QoS Provisioned Routing in Opportunistic Wireless Network”, is to develop a robust routing strategy for adaptive wireless networks. The initial phase involves predicting the movement of nodes in order to predict their future positions. The next step is the selection of relay nodes, which are used to transmit data and improve the performance of the routing protocol. This proposed routing system enables the effective transportation of packets with minimal loss. The Markov Chain model is employed to predict the random-based mobility of nodes. The next article titled “On Performance Analysis of Wireless Network over Double Shadowed Rician Fading Channel” investigates the performance of a double-shadowed Rician fading channel. This channel incorporates both dominant shadowing and scattering, or secondary shadowing, as shown by the Nakagami distribution. The outage probability, channel capacity, and average bit error rate (ABER) of BPSK, DPSK, MQAM, and NCBFSK modulation schemes are assessed for both coherent and non-coherent modulation techniques over double-shadowed Rician fading channels. In “Performance Evaluation of MIMO-OFDM-FSO with Modified Receiver,” the performance of a free space optical communication system using MIMO-OFDM with a modified receiver structure is evaluated. Closed-form expressions of average bit error rate and throughput are used for equal gain combining. Simulations assess throughput and bit error rate (BER) for the proposed MIMO-OFDM-FSO-MR model under varied turbulence and weather conditions. In “Topology Control of Drones Using Bio-inspired Hybrid Firefly-Grasshopper Algorithm for Searching Intruder Unmanned Aerial Vehicle,” a BHFG algorithm is proposed for cluster formation and head selection to communicate with the Ground Base-station (GS) and manage the drones’ rapidly changing topology. Data is transmitted correctly between cluster members using an effective topology-based routing technique. The paper, “Turbo Coded MIMO-OFDM Channel Estimation using Chaotic Grey Wolf Optimizer and Genetic Algorithm”, proposes a Turbo Coded multiple input multiple output-orthogonal frequency division multiplexing channel estimation algorithm. To improve bit error rate (BER), the turbo code reduces channel frequency domain maximal correlation. The channel is evaluated using LS-MMSE and Chaotic Grey Wolf Optimizer (CGWO), then paired with genetic algorithm to scale the optimal channel for error reduction. Encoding and decoding for LS channel estimation use Turbo-codes. The proposed method’s performance is then assessed using several measures.
This issue has eleven articles that pertain to the field of electromagnetics. In “A Compact SE-DGS Tapered-Fed Notched UWB Antenna Integrated with Ku/K band for Breast Cancer Detection,” a compact UWB antenna with X- and ITU-band notches is shown. The Ku and K bands are covered by this single C-type reflector antenna. The SEDGS antenna is ideal for portable wireless applications due to its small size, high VSWR value at the notch centre frequency, high peak radiation efficiency, single notched element blocking both X- and ITU-8 bands, stable radiation patterns, constant group delay, isolation of < -35 dB, and linear phase characteristics in the time domain. By comparing S21, current levels, and particular absorption rates with and without tumours, the suggested antenna tests its breast cancer tissue detection ability. “A Dual Port Hybrid Super-wideband MIMO Antenna with Diminished CCL and High BDR for IoT Applications” is the title of the next paper, which presents the design and analysis of a straightforward hybrid dual port skull-shaped super wideband Multiple Input Multiple Output (MIMO) antenna that features improved isolation. The impedance bandwidth and radiation characteristics of the proposed antenna are improved through the combined utilisation of the triple elliptical inclined slot and DGS. Deteriorated isolation characteristics, which are the key bottleneck for such MIMO schemes, are significantly improved in the proposed design by using a corrugated T-shaped strip decoupling plane. The antenna under consideration possesses the capability to be integrated into a multitude of wireless communication technologies that are associated with eMBB applications, such as 5G millimetre wave, augmented reality, virtual reality, and Internet of Things applications. The authors of the paper “A Hybrid Fractal Metamaterial Antenna for Wireless Applications with Gain Enhancement” describe a hybrid fractal multiband antenna laden with metamaterials that possesses gain enhancement properties for wireless applications. To increase the gain, a frequency selective surface (FSS) is implemented as a reflector beneath the antenna design. The authors present a complementary concentric open-ring microwave resonator sensor in their article “A Planar RF-Sensor Using Concentric Complementary Open-Ring Resonator for Dielectric Characterization & On-Field Testing of Soil.” This sensor is designed to provide precise measurements of the moisture content and electrical properties of soil. In order to increase the gain of all operational bands, this research titled, “A Reconfigurable Octa-Band Antenna with a High Gain for a Variety of Wireless Applications”, introduces an ultra-wideband reconfigurable antenna with a single FSS reflector. The suggested antenna addresses the need for wideband communication because it would be utilized for applications such as GSM, WiMax, 5G MID BAND, WLAN (C-BAND), WLAN (S-BAND), 5G (C-BAND), STM link-1, and UWB. The authors examine a low-profile, simply-structured, broad-band circularly polarised antenna that is appropriate for fifth-generation sub-6 GHz applications in their study, “Circularly Polarised Parasitic Strips Loaded Broadband Printed Antenna for Sub-6 GHz (n77/n78/n79) Domain.” Its design consists of two diagonally opposed symmetric parasitic strips coupled by a feedline, which allows for the simultaneous achievement of a broadband CP bandwidth and a wide impedance bandwidth. The antenna’s basic design and high AR bandwidth make it a promising choice for many wireless networks. The authors of the paper “Design and Investigation of Low Pass Filter with High Selectivity and Ultrawide Stopband” describe how they used tapered stepped impedance resonators to create an ultra-wide stopband low pass filter. An ultra-wide stop-band with a higher attenuation level is made possible by two circular slots in the ground and four open stubs. They extract, analyze, and validate the distributed counterpart of the proposed stepped impedance LPF using both simulated and real data. For front-end RF applications, the proposed LPF may be very helpful in rejecting unwanted and spurious frequencies. In the next paper titled “Design of a Wideband Flower-like Shape Metamaterial Reflectarray Antenna” authors propose the design of a planar reflectarray antenna that incorporates new meta-material unit cells. The structure displayed exhibits a noteworthy level of radiation efficiency. The proposed structure is characterized by its compact width, limited number of cells, and the absence of a trial and error process. The suggested approach is applicable to a reflectarray antenna that exhibits a gain between the 20 to 30dBi range, while maintaining a satisfactory level of radiation efficiency. The authors of the research titled “Gain Enhancement of Meta-material Inspired Multiband Antenna for Wireless Applications” propose the construction of a slotted octa-band antenna that incorporates meta-material cells. The antenna utilizes a slotted patch and ground approach to enhance its gain. The antenna has the ability to cover eight wireless communication applications, including IoT applications and several wireless standards. The next article, titled, “Gain Enhancement of Millimeter Wave Antenna by Ultra-thin Radial Phase Gradient Metasurface for 5G Applications”, presents a method for enhancing the performance of a microstrip antenna (MSA) operating at 28 GHz. The method involves the use of a phase graded index lens, which is both cost-effective and efficient. The researchers have developed a metamaterial array consisting of radial phase graded lenses with variable impedance and locally varying refractive index. This array is able to produce a directive beam in the 5G frequency range. The authors of the research, “UWB Disc Monopole Antenna: Time-Domain Characteristics during Transmission and Reception”, examine the time-domain effects of a UWB disc monopole antenna when used as a transmit antenna, receive antenna, and transmit-receive antenna pair. They explore these effects by employing various types of signal excitations. The objective of this study is to eliminate any uncertainty in the time domain response by considering the transfer function.
There is one paper on optoelectronics in this issue. This article, titled “High-speed VLC Security System using Two Key Services by Multi-point Analysis,” provides a new encryption strategy aimed at safeguarding data integrity, accessibility, and authenticity against threats from the Internet of Things (IoT). The K2 algorithm is proposed as a means to enhance the security level. It achieves this by employing the Henon algorithm for image transformation and the 2D key management logistic algorithm.
Various aspects of computers and computing are covered in 23 papers of this issue. A Bengali dataset for classification and clustering is presented by the authors in their paper, “A 2-Tier Bengali Dataset for Evaluation of Hard and Soft Classification Approaches.” The two tiers of this dataset’s architecture are used for hard classification methods on the first tier and soft classification methods on the second. While soft classification approaches use unsupervised learning based models for document clustering, hard classification techniques use supervised learning based models for document classification. There are various frameworks available for assessing the dataset’s first and second tiers independently. This next research presents a comparative examination of these algorithms with respect to the suggested dataset. The authors integrate hybrid energy sources, such as solar and wind energy, with the traditional dynamic economic emission dispatch (EED) problem to formulate a new model, namely complicated constrained hybrid energy integrated DEED problem, which may be able to generate less polluted power than the traditional DEED problem. This is described in the paper, “A Novel Quasi-Oppositional Learning Based Chaos Assisted Sine Cosine Algorithm for Hybrid Energy Integrated Dynamic Economic Emission Dispatch.” Chaotic dynamics and quasi-opposition learning (QOL) are incorporated into a novel sine cosine algorithm (SCA) in order to increase its convergence and diversity. In the following paper “A Unified Lightweight CNN based Model for Disease Detection and Identification in Corn, Rice and Wheat” suggest a single lightweight CNN-based model that can be utilized to identify diseases in the three most important crops: corn, rice, and wheat. The model under consideration employs convolution layers containing variable-sized filters at a single level in order to detect diseases with infected areas of varying sizes with precision. The proposed model’s enhanced performance metrics and compact size render it a feasible option for the detection of agricultural diseases in real-time, even in environments with limited resources. The work titled “A Weighted Deep Ensemble for Indian Sign Language Recognition” focuses on the development of a system that can recognize Indian Sign Language (ISL) using a wearable device worn on the forearm. The purpose of this system is to aid individuals who are hearing impaired. An innovative combination of convolutional neural networks (CNN) is suggested to achieve reliable recognition of Indian sign language (ISL) by utilizing data frommany sensors. The classification accuracy of 50 ISL signs improved from the previously achieved results. In the paper titled “An Efficient Capacity Based Routing Technique on MEDA-Based Biochips,” the authors offer an approach that may be used for various complex bio-assay activities to achieve 100% routing operation in MEDA-based biochips. The MEDA-based architecture allows for the flexible routing of droplets of varying sizes, resulting in improved accuracy and ease. The suggested method utilizes the best-fitted values of FPM movement for selection, and the second phase generates optimized outcomes depending on the edge capacity. Furthermore, by employing critical zone avoidance through the use of SPM, the droplet’s aspect ratio is preserved. The authors of the next paper “An Optimal Reinforced Deep Belief Network for Detection of Malicious Network Traffic” introduce the DSO-RDBN architecture for the purpose of classifying network traffic. The efficacy of the suggested method in categorizing the traffic data is assessed by examining various performance metrics including accuracy, precision, sensitivity, F-measure, and false alarm rate (FAR). The analysis is conducted to classify data into normal and abnormal categories. The result analysis indicates that the categorization of normal data has yielded superior outcomes in comparison to the classification of abnormal data. The authors of the manuscript titled “ANN-Based Statistical Computation for Remote End Fault Monitoring of the IEEE 14 Bus Microgrid Network” utilize fog computing to supervise remote end faults within an IEEE-standard 14 bus microgrid network. This is achieved by analyzing statistical parameters derived from Discrete Wavelet Transform (DWT) assessment. An examination of the currents coming out of various generator buses is conducted when L-G and L-L failures occur on the load-buses. Based on this evaluation, a set of rules has been created that produces satisfactory outcomes. In “Approach for Detecting Junctions in Roundabout using Map Data,” authors describe a method for locating roundabout intersections. They link roadways at node intersections. The junction of a roundabout is where roads enter or exit. The author retrieved all closed loop junctions and ran machine models on domain-known junction connection features. By dividing the dataset based on travel direction, 81 per cent detection of junctions was achieved. In the research, “CNN-OLSTM: Convolutional Neural Network with Optimized Long Short-Term Memory Model for Twitter based Sentiment Analysis”, authors propose sentiment analysis using CNN-OLSTM. The method includes pre-processing, word2vec conversion, and prediction. The CNNOLSTM classifier classifies tweets as positive or negative using the retrieved vectors. CNN uses max-pooling and convolutional layers to minimize input vector dimension. Also, the LSTM model can detect long-term word sequence dependencies. For better LSTM performance, the rain optimization algorithm (ROA) is employed. The CNN-OLSTM method surpasses deep neural networks in accuracy. Assessment systems are often enhanced with EDM approaches, according to the authors of the next paper “Cognitive Evaluation of Examinees by Dynamic Question Set Generation based on Bloom’s Taxonomy.” The development of an assessment system that differentiates applicants according to their capacity to respond to intellectually demanding questions, rather than focussing on obtained marks is an uphill battle. In order to create an outcome-based online examination system that accurately assesses a candidate’s cognitive competencies, this study proposes a novel mechanism for dynamically ranking the applicants. In the paper, “Detection of Bacterial Spot Disease in Bell Pepper Plant Using YOLOv3”, authors successfully implement the detection of the most commonly occurring disease in Bell Pepper plant, the Bacterial Spot by using YOLOv3 (you only look once). By using YOLOv3, multiple diseases can be detected on the image of a single leaf. The identification results show a mean average precision of 90%. This paves the way for increasing agricultural productivity. The purpose of the research article titled “Diagnosis of Covid-19 using Chest X-ray Images using Ensemble Model” is to establish a correlation between the presence of the virus and images obtained from CT scans and chest X-rays. Data enhancement and preprocessing of CT scan pictures are part of the suggested system. Following this, the identical procedure is performed on chest x-ray images; it then compares the assessment metrics across the models and recommends the optimal combination of CT scan and chest x-ray for improved accuracy and results. The article “Finding Experts in Community Question Answering System using Trie String Matching Algorithm with Domain Knowledge” presents an innovative approach for identifying knowledge workers on community question answering websites by combining domain expertise with an exact string-matching algorithm. User profile modelling, question pre-processing, and expert recommendation are the three stages that make up the suggested system’s design. This study employs the use of the question-answering website stack overflow as a community resource for conducting tests. The system’s performance is evaluated, and the findings section demonstrated that the system obtained a higher accuracy rate. “Graph Laplacian for Heterogeneous Data Clustering in Sensor-Based Internet of Things” proposes a method for accurate heterogeneous data clustering, taking into account the importance of clustering. To get data points that are related to each other, authors use weight graphs to create a Graph Laplacian matrix, which takes use of the data’s correlation structure. Accurate clusters based on distance are additionally obtained using Eigen values. After being tested on five distinct real-world datasets, the suggested method proves to be more effective than the majority of the other options. The authors of the research, titled “Improved Precision Crop Yield Prediction using Weighted-Feature Hybrid SVM: Analysis of ML Algorithms” utilize multiple machine learning (ML) methods to forecast the yield of “rice and sorghum (jowar)” throughout two Indian seasons. This research presents a new method that combines Support Vector Machine (SVM) and Random Forest (RF) to accurately estimate agricultural productivity. The method utilizes a weighted feature approach to improve efficiency. The work titled “Integrating a Two-level Reinforcement Learning Process for Enhancing Task Scheduling Efficiency in a Complex Problem Solving Environment” introduces a novel method for task scheduling using a 2-level reinforcement learning algorithm. The method employs a stage of deep-intensive learning to create a strategy that can be implemented for mapping tasks to resources. The mapping is reassessed at predetermined execution breakpoints, and the approach is reevaluated based on the incremental learning derived from these breakpoints. The proposed technique exhibits consistent performance across all datasets. It is suggested in the paper “Low Cost Smart Irrigation for Agricultural Land Using IoT” that smart cell phone use can be utilized for setting up irrigation in fields that use the solenoid valve start and stay method. The tool mentioned in this paper is less expensive and can work in soils that are different temperatures and levels of moisture. This gadget is fully Android cellular software and uses IoT to water land to make crops grow better. The authors of the research titled “Network Reconfiguration for Searching Maximum Loading Capacity Radial Network: An Efficient Graph Theory-Based Machine Learning Approach” suggest a combination of machine learning and graph theory to find the best radial configuration. Graph theory is employed to confirm radiality, while the machine learning model predicts the average CPF parameters of all nodes. The concept that was suggested worked well when tried on a 30-node mesh-style distribution system to find the best system configuration. In the research paper titled “Optimal Power Flow using a hybrid Improved Harris Hawks Optimisation Algorithm-Pattern Search Method,” the authors introduce the hIHHO-PS technique, which has been effectively utilized to address different optimal power flow (OPF) problems. These problems include the minimization of NAPGFC, TPL, SCC, VD, and the maximisation of SW and LF, each with varying levels of complexity. Authors developed a global BloomFilter routing system in “Research on Global Bloom Filter-based Data Routing system of Deduplication in Cloud Environment.” This paper proposes a data routing strategy based on global BloomFilter, which uses the client-server maintenance of global BloomFilter to select the k smallest block fingerprint queries before sending BloomFilter array. Data transmission takes more system time than index query, so this paper avoids communication with storage nodes before sending data. This technique eliminates the need to communicate data fingerprint information to the storage node to determine the routing node, reducing system communication overhead. “Research on Key Method of Cyber Security Situation Awareness Based on ResMLP and LSTM Network” is a paper that looks at a new way to improve a cyber-security situation awareness method based on ResMLP and LSTM network. The work is mostly about analysing how cyberattacks work. It adds Residual Multi-Layer Perceptrons from deep learning to the structure of the long-term and short-term memory networks. It can successfully pull out the spatial and temporal features of network traffic data, make computations simpler, and raise the level of accuracy of cyber security situation awareness. In the research paper titled “Tie-Line Power Transferred: Data Security Using Block Chain Technology,” the authors use Block Chain technology to make sure that data that is sent over a tie-line can be monitored, tracked, and is impossible to change. In this study, the Nepanagar–Dharni Tie-line between the MP Electricity Board and the Maharashtra Electricity Board is looked at. Another example of a security issue with Block Chain Technology is a solar power plant that is linked to the grid and a consumer. Because decentralised blockchain technology is built in, the grid owner, the utility, and the user can all keep the privacy and security of the data set and image sharing for tie-line power transfers. Weibull distributive feature scaling multivariate censored extreme learning classification is used successfully for attack detection in IoT in the paper titled “Weibull Distributive Feature Scaling Multivariate Censored Extreme Learning Classification for Malicious IoT Network Traffic Detection.” The authors test the proposed method on the UNSW-NB15 dataset to see how well it works. The success indicators are looked at. The suggested WDGMS-MCP-ELM-AD-IoT method is more accurate and has a higher FMeasure than other methods.
Four articles in this issue deal with control engineering. In the first article titled “A Novel Flexible Method for Optimal Operation Modelling of Multi-carrier Energy Systems,” the authors talk about a new, adaptable way to make an energy supply system work at its best in all kinds of weather and seasons. They use load data, prices, constraints, and penalties to fit the suggested model, and then hub optimization helps them find the best way to run things and cut costs. The paper “A State Observer-Based Fractional Order Approach for Trajectory Tracking and Attitude Control of Quadrotor” presents a feedback control technique for quadrotor UAV trajectory tracking and flight control. In particular, a robust fractional order sliding mode control (FOSMC) method using state observer approach for position tracking and attitude control is proposed. To avoid chattering, state observer approach is chosen. “Design and Optimal Location of Power System Stabiliser in the Multi-Machine Power Network” is the next paper. It suggests using a damping torque index (DTI) to find the best place to put the power system stabilizer (PSS) in a multi-machine power network. For low-frequency electromechanical (LFEO) analysis of power systems, the suggested index is based on the classical damping torque analysis (CDTA) method. The highest magnitude of the DTI under normal operating conditions is used to choose the PSS location. The CDTA method is used to create the PSS, and then the phase compensation technique is used to change the factors that go with it. Results obtained on RTD real-time digital simulator (RTDS) show that the proposed approach efficiently damps low-frequency electro-mechanical oscillations. In this paper, “Frequency Control Strategy for Grid-tied Virtual Power Plant using SSA-tuned Fractional Order PID Controller”, the load frequency control strategy of a grid-integrated VPP with an independent control area that includes diverse Distributed Energy Resources is examined. After examining time-domain specifications and ISE objective function values, the SSA tuned FOPID controller outperforms PID and PI controllers. Sensitivity analysis of the proposed SSA tuned FOPID controlled system, taking into consideration load and parametric uncertainties.
This issue has seven papers that discuss the extensive subject of electronic circuits, devices, and components. The research titled “A Comparative Analysis of Cavity Positions in Charge Plasma Based Tunnel FET for Biosensor Application” examines and compares the performance of a charge plasma-based Tunnel FET. Specifically, the study focuses on the use of a nanogap cavity at the source, drain, and gate areas. An assessment has been conducted to determine the device’s sensitivity to various cavity positions, specifically in relation to ION, ION/IOFF, Vth, and SS, for both charged and neutral biomolecules. The authors show that the gate cavity DM CP TFET is a promising contender for applications requiring highly sensitive, label free biosensors. The researchers in their paper “A DFT Based Approach for NO2 Sensing Using Vander Wall Hetero Monolayer” used a special kind of two-dimensional (2-D) hexagonal Zig-Zag Boron Nitride nano-ribbon (hBNNR) to find Nitrogen dioxide (NO2). In this case, distorted structures like Al-doped, P-doped, and Stone–Wales defective structures are thought of as an electro-sensing material. They used an ab initio method based on first principle density functional theory (DFT) to look into the electrochemical properties of both pristine and distorted h-ZBNNR in presence of NO2. The work titled “Implementation of Novel Block and Convolutional Encoding Circuit Using FS-GDI” presents a new technique to implementing encoding circuits for error control schemes. The aim is to enhance the efficiency of data processing by reducing the complexity associated with encoding and decoding procedures. The authors of the paper “Improved Q Factor 3D Double Layered on Chip Resistor with Shielded Ground Conductor” suggest adding a shielded grounded conductor to a double-layered N-Well meander-line structure to improve the quality factor of on-chip resistors that are used at high frequencies. An extra shielding ground conductor is added to the suggested structure to cut down on induced capacitance coupling and substrate losses. This is done to improve the Q factor even more. The authors of the paper “Investigation on RF/Analog Performance in SiGe Pocket n-Tunnel FET” have developed a SiGe pocket n-TFET and analyzed its electrical performance using a TCAD simulator. The authors have described an n-TFET in which a SiGe pocket is placed between the source and the channel to facilitate vertical tunnelling. This arrangement increases the rate of tunnelling at the junction between the source and the channel. Intrinsic SiGe pocket TFETs are shown to be a promising device for analogue and high frequency applications at x = 0.5. The research titled “Neural Network based Fast and Intelligent Signal Integrity Assessment Model for Emerging MWCNT Bundle On-Chip Interconnects in Integrated Circuit” aims to model and analyze MWCNTB as on-chip interconnects using neural network techniques. This study investigates the application of machine learning (ML) and neural network (NN) approaches to analyze signal integrity and quickly compute on-chip interconnect design. The authors of the paper “Nodal State Comparison-based Dynamic Hold Technique for Low Power OR gates in Domino Logic” describe a Nodal State Comparison with Dynamic Hold Domino (NSCDHD) circuit technique that can be used to build OR gates in domino logic. Comparing the results, the suggested design uses a lot less power and can handle a lot more noise compared to two new circuit techniques: the Clock Delayed Dual Keeper and the basic domino structure technique, also known as Leakage Current Replica Domino.
One article from the field of instrumentation and measurement is included in this issue. As GNSS Real Time Kinematic (RTK), becomes more popular in real life, this study, “Single Baseline Long Distance RTK using CLS GNSS Module and Open-Source Software: A Case Study from India,” looks at how low-cost, small, low-power, single-frequency (CLS) GNSS modules can be used with open-source RTK processing software to make single-baseline, long-distance RTK more cost-effective by taking advantage of multiple GNSS satellite signals.
Four articles in this issue cover the expansive topic of medical electronics. The authors of the paper “Automated Diabetic Retinopathy Grading based on the Modified Capsule Network Architecture” suggest a way to improve the accuracy of Diabetic Retinopathy detection and classification by combining Caps Net with SVM. Caps Net is a good choice for this work because it can successfully classify a smaller and less balanced data set. However, Cap’s Net performance is restricted to recognizing the nearly placed objects that are identical. Dental radiographs and photographs are used in the paper titled “Casualty Identification with Dental Radiographs And Photographs” to demonstrate a dental biometric method. In cases where radiographs are not available, the goal is to use photos to help identify casualties. It is suggested that shape descriptions and skeletons be used to improve the performance of shape extraction. One gets data from the test image and compares it to a set of database images. The best match is chosen for authentication. The article “Microfabrication and Characterization of Chemically Actuated Implantable PLGA Reservoir-based Device for Controlled Drug Delivery” describes the fabrication and characterization of a new biodegradable implantable drug delivery device that is easier for users to conform to. Utilizing Micro-Electro-Mechanical Systems (MEMS) technology in this study led to a smaller gadget size, which creates new ways to deliver drugs. Analysis both in vitro and in vivo showed that the device could be useful. For example, insulin (the model drug) doesn’t break down or get affected unless the membrane is disrupted. This clearly shows that the implantable device has a protective property that makes the drug work better. Authors suggest a novel Morph-Rec model for liver segmentation from CT images based on morphological reconstruction operation in their paper titled “Morph-Rec: A Novel Computer-Aided Liver Segmentation Model Based on Morphological Reconstruction Operation.” The goal of the proposed study is to segment the liver region from the CT slices, regardless of the liver region’s dimensions. The proposed technique can facilitate and simplify the liver lesion detection process by defining the liver region’s boundary in the CT image, and assists physicians in virtual surgery simulation and performing liver transplants.
There are many papers in this issue -21 from the power electronics field. A power-factor-corrected based flyback converter for low-power home lighting is described in the first paper, “A Highly Efficient PFC Flyback Converter for Residential Lighting with Universal Input.” The suggested flyback converter offers improved power-quality (PQ) performance while operating in discontinuous-conduction-mode (DCM). The flyback converter has many advantages over non-isolated converters in low-power domestic lighting, including a lower component count, an affordable solution, and safe working conditions. The next paper “A Hybrid BCMPO Technique for Optimal Scheduling of Electric Vehicle Aggregators under Market Price Uncertainty” suggests a method that combines the work of a political optimizer (PO) and a balancing composite motion optimizer (BCMO). This is why it is called a BCMPO technique. The optimization system is suggested as a way to deal with the unknown price of energy and come up with a solid schedule for the electric vehicle aggregator. To show how uncertain market prices are with the BCMPO method, the highest and lowest upstream grid prices are used. The suggested algorithm makes it possible to create a number of charging and discharging methods that the operator can use for stable EV aggregator scheduling even when the upstream grid price is unknown. The subsequent paper titled “A New 29-level Switched-Diode Multilevel Inverter with Optimal Device Count” introduces a new single-phase multilevel inverter (MLI) topology with 29 levels, using asymmetrical switched-diode configuration. The implemented topology is capable of producing a maximum of 29 levels of output voltage by utilizing unequal DC sources. The suggested configuration minimizes the number of circuit components, overall dimensions, and expenses of the system. In addition to the various advantages of MLIs, accuracy and reliability are crucial due to the presence of a higher number of components, which helps in reducing the total harmonic distortion (THD) value. This can be seen as a significant endeavour aimed at enhancing dependability while maintaining the optimal THD value. In the paper titled “A Novel Emergency Lighting System Design Eliminating Extra Phase Line Installation”, the authors provide a design for an Emergency Lighting System (ELS) that avoids the requirement of installing additional phase lines by utilizing power line communication (PLC) circuitry. Moreover, LED lamps are favoured over fluorescent lamps due to their numerous benefits. The planned ELS system is designed to identify emergency situations and power outages. The system’s battery is subsequently recharged utilizing PLC technology. The authors of the work titled “A Power Control Scheme for a Wind Turbine/Fuel Cell Hybrid Power System with DFIG-DC link Topology” discuss the design, simulation, and hardware of a power control scheme for an on-grid hybrid system that combines a wind turbine and a fuel cell using a DFIG-DC link configuration. In order to optimize the power output of the wind turbine, the DFIG-DC system is simulated and a Stator Field-Oriented Control (SFOC) strategy is used. The system performance was verified using an experimental test bench equipped with a dSpace DS1104 processor board. The next article “An Advance Control of Grid Integrated Wind Turbine Driven DFIG-Battery System with Grid Power Shaping Under Gust Wind Variation” talks about a wind energy conversion system (WECS) that uses a doubly fed induction generator (DFIG) and a vanadium redox flow battery (VRFB) in the DC-link. It also talks about a bidirectional DC-DC converter that keeps the DC-link voltage constant. This helps keep the grid’s power balanced and smooth even when the wind is blowing in gusts. Data from real-life installations were used to come up with a way to build the VRF-based BESS. It has been shown that the proposed PLL works well even when there is dc shift. The research, titled “CT-Type MLI based PV System for Critical Loads using SIMO DC-DC Converter”, introduces a photovoltaic system that may provide continuous power to critical loads in the case of faults or extreme weather conditions such as cyclones, when the grid supply is disrupted. The suggested design utilizes the CT-Type MLI and the SIMO DC-DC converter to establish the critical load power supply system. The CT-Type MLI outperforms other topologies in terms of TSV, cost factor, and device count, resulting in improved efficiency. The authors of the paper “Development of an Intelligent Control Strategy for a Hybrid Energy System Integrated with HEV Drive” suggest the use of a bi-directional DCDC converter and a storage system. This setup allows for the transfer of energy in both forward and reverse directions, from the energy source to the storage element, and from the storage element to the load end. This bidirectional energy transfer is achieved during the charging and discharging of the battery. Furthermore, the intelligent control system (ICS) not only carries out control activities, but also manages the drive control of Hybrid Electric Vehicles (HEVs) by regulating the grid connected inverter. The system is then subjected to testing using various standard driving cycles. The authors of the paper titled “Dual Output and Dual-Frequency Resonant Inverter-based Induction Heating using ADC control” provide a method to create a resonant converter that has both dual output and dual frequency (DODF) capabilities. This strategy aims to lower costs and enhance efficiency. The suggested configuration eliminates the requirement for a rectifier and additional AC link capacitors, resulting in a simplified circuit and making it suitable for contemporary induction heating applications. The authors of the following paper “Evaluation of Distinct EV Scheduling at Residential Charging Points in an Unbalanced Power Distribution System” describe a Multi-objective scheduling method for each candidate-based EV that will help power delivery in the best way possible. The goals are to minimize the difference in average demand and lower the system’s unbalance. A realistic three-phase power distribution system has been used to test the suggested method. The paper titled “Experimental Validation of Torque Ripple Reduction in MMC fed BLDC Motor using Proposed Phase Modulated Model Predictive Control” discusses the analysis of torque ripple in a brushless DC (BLDC) motor. To minimize the ripple, a phase modulated model predictive current control approach has been applied to the MMC fed BLDC motor. The suggested phase modulated model predictive control (PMMPC) technique improves the performance of the torque ripple of the BLDC motor. This is compared across several current control methods and switching frequencies. In the research titled “Frequency Stability of a Wind-based Energy System by Virtual Inertia Controller of an Inverter Connected to Grid”, the authors propose a non-linear controller based on fuzzy logic to replicate the behaviour of a synchronous generator. This non-linear controller effectively harnesses the energy from the moving blades of the wind turbine and maintains the necessary amount of inertia in the system to mitigate frequency variations. The article titled “Hardware Design and Implementation of FPGA Controlled 7-level Reduced Switch MLI” presents a proposal for the design of a seven-level reduced switch multi-level inverter (7LRS-MLI) topology. The design generates a waveform with seven levels for staircase output. This is achieved by using only seven power switches, resulting in cost reduction, smaller area, and improved performance. Specifically, it increases efficiency and effectively reduces switching loss. The study discusses the implementation and results of both symmetric and asymmetric configurations. The authors of their research “High-Power Converters and Challenges in Electric Vehicle Wireless Charging – A Review” look at different inductive and capacitive charging systems that can be used to build a high-power infrastructure. It is emphasized what makes SAE, ICINRP, and IEEE safety guidelines for wireless charging technology unique. Compensation circuits, resonant converters, and challenges associated with wireless power transfer (WPT) systems are explained. This study of electric vehicles (EVs) will help researchers and business people find and build new charging stations that are quick, cheap, and don’t take long to charge. The paper titled “Intelligent Short-Circuit Protection with Solid-State Circuit Breakers for Low-Voltage DC Microgrids” examines the issues associated with safeguarding low voltage (LV) systems and presents a protection approach using solid-state circuit breakers (SSCBs) for short-circuit incidents in DC― μGs microgrids. This methodology offers fault current limitation (FCL). In order to enhance the effectiveness of the suggested method, the traditional fault detection approaches that rely on fixed thresholds are substituted with an intelligent strategy that utilizes decision trees to acquire knowledge about the fault patterns in the system. The research titled “MMC based PV Fed STATCOM with Hybrid GA-RBFNN for PQ Enhancement” examines power-quality problems in a photovoltaic system that utilizes a STATCOM based five level Modular Multilevel Converter. This work utilizes an interleaved quadratic boost converter to amplify the output of the photovoltaic (PV) system over a broader range. A controller based on an Adaptive Neuro-Fuzzy Inference System is used to achieve fast, efficient, and flexible control of a DC-DC converter. The MMC plays a vital role in addressing power quality challenges due to its advantageous features such as scalability, power quality, and modularity. The authors of the paper, ‘Model Predictive Control of Transformerless Series Custom Power Device for Voltage Quality Improvement”, introduce a single-phase series custom power device (Se-CPD) that utilizes model predictive control (MPC) to mitigate irregularities in the supply voltage, such as voltage sag, swell, and harmonics. The control method for Se-CPD involves generating a reference voltage and appropriate switching signals for the voltage source inverter (VSI) of the Se-CPD. The extraction of the reference voltage from the distorted point of common coupling (PCC) voltage is achieved by synthesizing a second-order generalized integrator (SOGI) that does not introduce any phase delay, in contrast to the use of a low pass filter (LPF). An MPC method is used to generate optimal switching signals for Se-CPD. This implementation is intuitive and straightforward, without the need for a modulation stage. The MPC algorithm takes into account the converter’s switching characteristics. The research project titled “Modified Bridgeless PFC based Cuk-Sepic Converter with Better Power Quality for Arc Welding Applications” focuses on a new type of single-phase Cuk and Sepic power factor correction converter that is specifically designed for arc welding. The recommended converter is designed to operate in DCM mode, effectively handling fluctuations in load voltage and supply voltage to optimize performance. The control method incorporates a voltage loop to guarantee stability in the arc welding process and enhance the quality of the input power. The paper titled “Nonlinear Fractional Order Model Identification of the Voltage Source Inverter Fed Induction Motor” aims to accurately identify the nonlinear behaviour of the VSI-IM model by employing the PWM signal injection method. The fractional-order VSI-IM model is useful for gaining a deeper understanding of the dynamic behaviour of the induction motor (IM) drive in speed controller design, both for sensorless and sensored systems, as well as in predictive controls, whether they are model-based or model-free. The fractional VSI-IM models are characterized or determined at low, medium, and high frequencies. In the manuscript, “Path Planning of Unmanned Aerial Systems for Visual Inspection of Power Transmission Lines and Towers”, a decisive flight path planning for Unmanned Aerial Systems (UAS) to visually inspect a power transmission line and towers are explained. The objective of this paper is to maximize the performance of three functions such as, coverage of transmission tower, quality of captured image and flight time. Secondly, proposing an automated inspection strategy for UAS in order to follow the overhead power transmission lines. The objective of the study titled “Solar Power Estimation methods using ANN and CA-ANN Models for Hydrogen Production Potential in Mediterranean Region” is to uncover the capacity for generating and storing hydrogen in areas characterized by high solar radiation. The photovoltaic panel system harnesses energy to generate hydrogen through the alkaline electrolysis system. As a result of the sporadic characteristics of solar energy, the energy derived from solar panels experiences continuous fluctuations. During adverse conditions, the energy generated by solar panels diminishes. It is crucial to store energy alongside the electrolysis device in this scenario. This study showcases the ability to estimate the potential for hydrogen production using artificial intelligence-based approaches. The assessment is based on real data collected from a solar PV system.
Additional information
Notes on contributors
Ranjan K Mallik
Ranjan K Mallik is a 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), the Asia-Pacific Artificial Intelligence Association, and the Artificial Intelligence Industry Academy. 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 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. Corresponding author. 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 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]