https://orcid.org/0000-0003-1761-217X
The current issue of the IETE Journal of Research (Vol 69, No 4, April 2023) contains 50 articles. These articles present ongoing research and developments taking place in the broad areas of Biomedical Engineering, Power Systems, Electromagnetics, Computer Science, Electrical and Electronics Engineering and Microelectronics.
The well-known Wien network for single-component frequency control is redesigned in the first paper in the issue, "The Conventional Wien Network for Single-Component Frequency Control," by using a potentiometer in place of the two fixed resistances as used in a Hall network. The paper presents an analysis of the simpler proposed network, and the peak frequency and the peak value are calculated and discussed.
The authors of the following paper, "Performance Improvement of Quantum Well Infrared Photodetectors through Dark Current Reduction Factor," present an analytical model for calculating the signal-to-noise ratio (SNR) and dark-current reduction factor of quantum well infrared photodetectors (QWIP). By adjusting the device parameters, such as the distance between the wells, the bias voltage, and the operating temperature of these detectors, the goal is to decrease the dark current and enhance the SNR. The model is used to draw inferences regarding the dependencies of dark current in QWIP as function of number of quantum wells.
In the paper titled "Improving the Performance of Classifiers by Ensemble Techniques for the Premature Detection of Unusual Birth Outcomes from Cardiotocography," the authors propose techniques to reduce the infant mortality rate during the early stages of pregnancy. The fetal heart rates from subjects were compiled into datasets. The authors used the datasets, and classifiers such as K-nearest neighbour, Decision tree, Naive Bayes, and Random forest machine to classify normal, suspect, and pathologic cases. Inferences are drawn from the study regarding the efficacy of classification.
The next paper “Deep Learning Base Face Anti-Spoofing - Convolutional Restricted Basis Neural Network Technique" presents an improved method for anti-spoofing based on 3D Convolutional Restricted Basis Neural Network (CRBNN). The 3D-Convolutional layer is used to map the input image's characteristics. The experimental results demonstrate the efficacy of CRBNN in terms of accuracy, Equal Error Rate, and runtime compared with existing methods such as spatial pyramid coding micro-texture, Convolutional Neural Network, and radial basis network (RBFN).
The authors of the following paper titled "Enhancing the Output Power of the Partially Shaded PV Array Using the Corona Virus Optimization Algorithm" present a method for reconfiguration of photovoltaic array system generates, resulting in shading spread across the array, which increases its power output. In the conventional method of reconfiguration, the physical position of the modules is maintained, but their electrical connections are altered based on the irradiance level. The proposed Corona Virus Optimization Algorithm (CVOA) method has been evaluated with TCT and SuDoKu patterns on 6x 6 arrays subjected to varying shading conditions. The paper presents comparison of CVOA algorithm with reconfiguration methods and inferences are drawn from the study.
The authors of the next paper, “Novel Network for Medicinal Leaves Identification" present a plant classification algorithm based on deep convolutional neural networks. The classification system named AousethNet is a modification of AlexNet in which the SoftMax layer is replaced with Majority vote classification. It is trained to predict the plant species based on a massive number of leaf samples from four datasets: Mendeley, D-Leaf, Flavia, and Folio. AousethNet's classification performance is reported and discussed in the paper.
The following paper on “Memory-Efficient LFSR Encoding and Weightage Driven Bit Transition for Improved Fault Coverage” describes a memory-efficient encoding-based technique for generating test patterns for a given primitive polynomial Linear Feedback Shift Registers. The generated test patterns are divided into groups and encoded to produce multiple test patterns. A feature of the test patterns is to reduce dynamic power as well during testing process. The paper discusses the experiments on ISCAS '85 and a portion of ISCAS '89 sequential benchmark circuits to demonstrate its efficacy in terms of memory efficiency and hardware complexity reduction.
The objective of the research described in the paper "Machine Learning Model for Breast Cancer Data Analysis Using Triplet Feature Selection Algorithm" is to increase the accuracy, sensitivity, and specificity while decreasing the False Positive Rate (FPR) and False Negative Rate (FNR) through feature selection for aiding in cancer diagnosis. The paper reports utilizing the effects of triple feature selection algorithm with the logistic regression classifier on the performance. The performance is also compared to that of existing feature selection methods and classifiers. The paper reports accuracy, FPR, FNR, sensitivity and specificity of classifier in identifying benign and malignant cells.
The research described in the following paper, titled "Implementation of a Novel TABGD-BBCO Controlling Mechanism Used in EV Systems," pertains to developing a controlling mechanism named as Tuple Accelerated Batch Gradient Descent (TABGD) to improve the speed control of electric vehicles. This technique provides ability to control the converter and inverter circuits by setting the parameters of the controlling mechanism so that they work best. A modified Batched Bee Colony Optimization algorithm is used to provide the EV system with optimal battery power support. The paper reports the performance of the proposed mechanism that is validated with experiment data and compared with other methods from research literature.
Several physical systems, such as transformers, sensors, and biomaterials, are examined utilizing the ladder network model's equivalent in the paper "Impedance Parameters Estimation of an RLCM Ladder Network Using Subspace and Similarity Transformation Approach". The presented approach solves the nonlinear parameter estimation issue linearly and without an initialization step. It overcomes problems of ill-conditioning of the non-linear optimization algorithms. The ladder network presents complexity due to the mutual inductances between a transformer's various winding sections. The research reports investigation of a ladder network model of a transformer's winding. Using the simulation results of a six-section transformer ladder network, the proposed algorithm’s performance is inferred and reported.
The paper titled "Mathematical Modelling and IoT Enabled Instrumentation for Simulation & Emulation of Induction Motor Faults" presents the development of a system to simulate and emulate faults in embedded system-based induction motors. The induction motor faults are mathematically modeled based on the motor current signature and vibration frequency spectrum, based on theoretically derived expressions. The features of the proposed method are low-cost, portable, and convenience of the evaluation tool for motor condition monitoring products. It is based on Intel Atom Minnow Board and digital storage oscilloscope. The paper reports study of simulated and emulated fault signals for three phase induction motors and provides evaluation against standards.
In the paper "Extended Boost Switched-Embedded-Capacitor Inductor ZSI with Low Voltage Stress on Capacitors and Soft-Start Capability,” the authors report the study to increase the boost factor of a Z-source inverter (ZSI) with a switched-inductor structure. The conventional and proposed inverters structures are investigated to determine their governing relationships. The paper reports the PSCAD/EMTDC based simulation comparisons of boost factor and voltage across capacitors in the conventional and proposed inverters. The paper also reports the evaluation of results using prototypes of the proposed inverters to draw inferences.
The paper titled, “Three-Level Hybrid Boost Converter with Output Voltage Regulation and Capacitor Balancing” presents a three-level hybrid boost converter with output voltage regulation and capacitor balancing. A boost converter and single-phase three-level T-type neutral-point-clamped inverter form the converter. The converter has two capacitors, one inductor, four discrete power switches, and four diodes. Two triangular carriers and modulation indexes generate pulse-width modulation signals. The paper reports the modeling of the converter using Plexim's PLECS and its simulation and experimental studies of steady-state and transient performance using a prototype converter.
In the paper “Small Offset Reflector with Matched Feed for 5G Application” the authors propose a two-layer microstrip matched feed for a compact offset reflector with projected diameter equal to 10λ, operating at 3.5 GHz. Details of the structure and its analysis are presented in the paper. The proposed feed consists of a rectangular patch operating in dominant mode at the top layer and a circular patch operating in TM21 mode below it. The paper presents the simulation study of characteristics of the proposed matched feed. These results are compared with the measured results of a fabricated prototype and inferences are drawn from this study.
In “Triple Band Notch Microstrip Patch Antenna with Fractal Defected Ground Structure” the authors present the design of microstrip patch antenna that is compatible in size with fractal defected ground structure (FDGS). The fractal structure of patch stub is useful in reducing the antenna size. A coplanar waveguide is used to obtain ultra-wideband capacity of the antenna. The antenna is fabricated for wireless application of emergency management applications. For investigating the band notching properties, slot of meander curve geometry and FDGSs are analyzed and discussed. The paper presents experimental tests on a manufactured prototype to examine the effectiveness of the antenna and draw inferences.
The following paper titled “Integrated Planar LTE MIMO Dual-antenna System on Laptop Computer’s Hinge” presents an LTE MIMO dual antenna system suitable for laptops. The structure covers LTE bands with antenna size of 50 × 5 mm2 printed on the FR4 substrate. The design integrates the metal hinges and ground plane into one of the antenna’s resonant paths, which reduces the size of the antenna. Other aspects of the design are presented. The radiation characteristics are presented. The measured isolation in the operating frequency band and measured antenna efficiency are presented from which inferences are drawn about the design.
The authors of the paper titled "Unsupervised Feature Selection Approach for Cancer Prediction" propose an algorithm for unsupervised feature selection from tissue data based on microarray DNA technology for the purpose of cancer prediction that is more independent of the class label. The initial step involves a feature ranking algorithm based on Single Value Decomposition (SVD)-Entropy. The correlation between attributes is then used to eliminate attributes/features that are highly correlated. The paper reports results of simulation experiments conducted on three distinct cancer datasets, including Ovarian, Lung, and Breast cancer. The accuracy scores that are obtained for these datasets are used to make inferences about the efficacy of the approach.
The next paper on “Fourier Transform and Autoregressive HRV Features in Prediction and Classification of Breast Cancer” discusses the use of the Fourier transform and autoregressive heart rate variability (HRV) features in the prediction and classification of breast cancer. Authors report recording and analysing spectral features of heart rate variability from 5-minute electrocardiograms of 114 breast cancer (BC) patients and 13 age-matched healthy controls for early diagnosis applications. ANN and SVM classifiers are used with the above features. The results of the study are reported and the efficacy of the different feature sets is discussed.
The authors of "Improving Three-Dimensional Near-Infrared Imaging Systems for Breast Cancer Diagnosis" report in the paper the possibility of better diagnosing tumors through the use of a three-dimensional imaging system that utilizes near-infrared light emission in breast tissue. According to their findings, the placement of the sources and detectors is crucial for making an accurate diagnosis of the abnormal region. The obtained results are reported to demonstrate that the abnormal area is detected with a much lower error rate using the proposed placement of sources and detectors. The paper also reports good results in the simultaneous diagnosis of two abnormal areas using the proposed placement of sources and detectors.
In the paper titled "Wideband Triple Sleeve Dipole Antenna with Loading for UHF Applications," the authors report the design of a miniaturized dipole antenna with enhanced bandwidth that incorporates triple sleeves and shorting load for 500 to 3000 MHz with no tuning requirement. At the lowest frequency, the antenna length is reduced by 51.5% compared to a half-wave dipole antenna by employing the idea of a triple sleeve and distributed shorting loads. The paper reports the simulation study of the antenna in CST Microwave Studio. It also presents measured results from a fabricated antenna and inferences are drawn from the results.
The following paper titled, “Automatic Liver Tumor Segmentation based on Multi-level Deep Convolutional Networks and Fractal Residual Network” deals with the problem of liver segmentation in medical CT images. It presents a practical upstream strategy based on a multi-level deep convolutional network (MDCN) and a fractal residual network (FRN) to separate the liver object from the rest of the abdominal cavity in a medical image. The MDCN is programmed to adapt to new data by assigning different probabilities to each super pixel based on where it is in the liver. Tumor regions are found using FRN, and the active contour model method is then used to refine the segmentation of the tumor. The paper presents results of study on CT images and comparison with competing segmentation techniques to draw conclusions about the proposed segmentation strategy.
In the paper "Performance Analysis of Radio Over Fiber System Employing Photonics Antenna and Different Modulation Schemes," the authors present an architecture for analysing the structure of a 2.4 GHz photonic antenna for a Radio over Fibre (RoF) system. The system uses a 16-quadrature amplitude modulation scheme and observations are made about data rate and fibre length of communication. The paper reports the quality of received signal as function of length and power of transmission for different types of fibres.
In the next paper, "The Text Mining and Classification Analyses of Tumor Based on Twitter," the author uses the text mining and classification method to look at tweets about tumors on Twitter. The aim is to understand public opinion focus on topics in social media. The study infers that random forests model did the best job amongst four different algorithms of figuring out the relationships between the keywords and how important they were. The study also found that Twitter users focused relatively more on surgery issues, psychological issues, and technical issues related to tumors.
In the paper "A Proposed Hybrid Model for Electric Power Generation: A Case Study of Rajasthan, India" the authors present a hybrid system comprising of solar, wind, MHD (magneto-hydrodynamics) and fuel cell, to exploit the advantage of each, and reduce the dependency on any one source. Several features are introduced in the hybrid system to address ease of use issues. The paper presents results from Simulink to demonstrate the technical viability of the proposed hybrid model.
The next paper on "Framework for the Restoration of Capsule Endoscopy Images Using Partial Differential Equations-based Filter" gives a design for noise reduction in capsule endoscopy images, which exhibit random noise, motion blur, and illumination-related degradations that reduce the efficiency of the computer-aided diagnosis system. The proposed noise-removal method is studied for its ability to reduce noise while preserving low-level and a few high-level components. The paper also presents results of a CAD system with and without restoration and draws inferences about the proposed design.
The authors of the following paper, "A Novel Energy-Efficient MIMO-OFDM Decoder Architecture with Error Detection," consider the problem of medical data transmission, in particular fetal ECG signal, using wireless communications while preserving their integrity and coherence. They discuss the use Chambolle-Pock based hybridised classifiers to separate the fetal ECG signal from noise during the early stages of transmission. The paper reports performance results with MIT-BIH Arrhythmia data and simulation software and inferences are drawn from the study.
The authors of the paper, "Design and Evaluation of an RFID Localization System based on Read Count," present an algorithm to improve the localization accuracy of an RFID system without the use of additional material. This algorithm is based on a probabilistic method that utilises only the read count (number of detections) of the reference and target tags. The measurements are performed in an indoor environment. The experiment results of the algorithm in the form of precision are compared with conventional algorithms to draw conclusions about the efficacy of the proposed algorithm.
The following paper titled "Investigation of Various Commonly Associated Imperfections in Radiofrequency Micro-ElectroMechanical System Devices and its Empirical Modeling," presents an investigation of the imperfections commonly associated with the realization of Radio Frequency Micro-Electro-Mechanical System (RF-MEMS) devices, as well as the empirical modelling of each associated phenomenon. The paper categorizes the imperfections into two classes viz. due to the physics of embedded device fabrication and due to IC assembly and packaging issues. Discussion about individual modelling of these issues is presented in relation to their effects on device performance.
The paper on “Utilizing Sneak Paths for Memristor Test Time Improvement” presents a method for testing memristor circuits for fault detection and fault diagnosis by taking advantage of a special feature of memristor crossbar circuits viz. sneak paths. Due to their non-volatility, high density, and low power operation, memristors are becoming a viable option for use in memory architectures, in-memory computing, and logic applications. The paper deals particularly with the “stuck-at-low” and “stuck-at-high” resistance faults for analysis. The paper presents the study of a 3 x 3 crossbar array for fault dictionary-based diagnosis. Inferences are drawn about the number of test-vectors required for given array size.
The authors of "X-Band Multilayer Stacked Microstrip Antenna Using Novel Electromagnetic Band-Gap Structures" describe the design of a multilayered rectangular microstrip antenna with inset feeding in the paper. It comprises of a 10 GHz resonating conventional microstrip patch and a novel 9x9 electromagnetic bandgap (EBG) array printed on a 0.5 mm thin FR-4 epoxy substrate. The authors present the simulation study that optimizes the patch and EBG surface dimensional parameters. The specifications and performance parameters of the antenna are presented and inferences are presented from these results.
In the next paper, "A Committee Machine Neural Network for Dynamic and its Inverse Modeling of Distortions and Impairments in Wireless Transmitters," the authors present a Mixture of Experts (MOE)-based committee machine neural network for modelling the PA/transmitter system transfer function and its inverse transfer function under different system conditions. At the broader level, the paper addresses the tradeoff between bandwidth efficiency and power efficiency with nonlinear distortion due to high power amplifier (HPA) in modern communication systems. The MOE network training is based on the maximum-likelihood criterion. The results of the proposed model show that it works well for generalisation with nonlinear HPA and memory effect when there are flaws in the system.
In the paper "LEARNING-based Focused WEB Crawler" the authors discuss the need to design an efficient crawler mechanism that yields appropriate and efficient search results for queries in order to overcome the problem of incorrect or inappropriate answers. A subjective comparison of different types of web-crawlers is discussed. The paper presents an architecture to mitigate these issues with a revised policy for web crawlers. A web crawler is presented that separates the URLs based on their frequency of page update and categorization into Static, Frequent, and frequently updated URLs to reduce the time for crawling at a given website.
The next paper titled "Anomaly Detection in Estimation of Load and Prediction of Load in Networked Control System Using Correlation and Regression Data Analysis," considers the problem of balancing of load on a networked control system as unbalanced load causes overloading of a network resulting in data loss or interruption in real-time control. The paper focuses on identifying factors and their dependence on load using correlation, as well as detecting an anomaly in network load. It presents with the aid of statistical regression data analysis, a mathematical relationship between load and network devices in order to predict the load. An example is discussed for numerical analysis, based on a segment of the Foundation Fieldbus network.
The following paper on "Fault Detection and Classification Scheme for Transmission Lines Connecting Wind farm using Single end Impedance," presents an algorithm for detecting and classifying faults in transmission lines under distributed generation condition. The algorithm uses wavelet transform coefficients to approximate the voltage and current signals over the course of a single cycle. The paper presents details of testing of the algorithm in a real-time digital simulator for nonlinear high-impedance faults in a wind farm environment. The performance for various fault types with the variation of pre-fault loading condition, line parameters, line length and source impedance is presented and discussed.
The authors of the paper "Decentralized Overlapping Control Design with Application to Rotary Drilling System" present the development of a state-feedback-based overlapping decomposition technique for controller design of rotary drilling systems. Using the expansion–contraction principle and Lyapunov theory, the global stability study of the decomposed system is given. The authors discuss the effectiveness of the technique in the context of high-frequency mode stick-slip vibrations data measured in a functioning rotary drilling system from an exploration well.
The next paper on "Opinion Mining on Integrated Social Networks and E-Commerce Blog" presents work in opinion mining and specifically a technique with a set of rules for integrating social network reviews such as those found on Twitter and Facebook with blog reviews such as Amazon reviews. The reviews are then mined to give prospective buyers and businesses a concise summary of reviewers' opinions on the products to enable customers to be better able to make informed purchasing decisions. The paper discusses how the proposed technique is able to improve sentiment prediction.
In the paper "Optimized Passive Cell Balancing for Fast Charging in Electric Vehicle," the authors are concerned about Battery Management System (BMS) for EV battery packs that ensures that cell voltages are kept constant regardless of the load. The authors present a method of passive-cell balancing attained using a variable balancing resistor based on the balancing current requirement during slow or rapid charging. The paper presents the results of evaluation of a passive system with a variable resistor output.
In the paper titled "Analysis of Climate Change and Its Impact on Health Using Big Data Analytics in Cloud Environment," big data analytics is used to investigate the topic and the effects of climate change on health. Big Data-related technologies have been used to look at the different extreme factors that are causing climate change and find links between them. One is to look at pollution data from different cities in the United States. The second method is Global Temperature Analysis, which uses datasets with different time lines. The third method is NCHS leading causes of death in the US, which uses demographic and medical information. The paper discusses several data sets and analysis to relate climate change to impact on health.
For optimal solar power management of a two-stage three-phase grid-integrated solar photovoltaic (SPV) system, the authors of the paper titled “Grid Synchronization and Islanding Detection Control Algorithm for Two-stage Three-phase SPV System” present an adaptive feedforward-feedback control algorithm. The control algorithm allows SPV energy to be fed to the load and the grid while also balancing grid currents, compensating reactive power, eliminating harmonics, and protecting the load and the source from damage in the event of an islanding condition. For the purpose of evaluating the efficacy of the algorithm, quantitative system analysis is presented and discussed.
In the paper titled "Analysis of Amplitude Scintillation and Positioning Error of IRNSS/GPS/SBAS Receiver for Heavy Rainy Days," the authors examine the characteristics of amplitude scintillation on an IRNSS/SBAS/GPS receiver with all seven satellites of the Indian Regional Navigation Satellite System (IRNSS) at the low-altitude station IITRAM, Ahmedabad, on days with heavy rain. The navigational precision of such systems can be impacted by intense scintillation, leading to inaccurate positioning services that is the subject of this paper. The authors report the relative scintillation effects on the different bands.
The next paper on "Multi-Objective Optimal Power Flow in Islanded Microgrids with Solar PV Generation by NLTVMOPSO," presents an optimization method with separate objectives for optimal dispatch of real and reactive powers from Distributed Generations (DGs) in islanded microgrids. Specifically, the optimization method is the Non-Linear Time Variation Multi-Objective Particle Swarm Optimization (NLTV-MOPSO). The paper presents results to demonstrate the efficacy of the proposed method for solving the multi-objective optimal power flow problem in an islanded microgrid.
In the paper "Model Order Reduction Based Power System Stabilizer Design Using Improved Whale Optimization Algorithm," the authors present an optimization technique viz. improved whale optimization for designing a power system stabilizer using model-order reduction for a modified single machine infinite bus system. The paper brings out the efficacy of the technique through eigenvalue analysis under different loading conditions. It also reports simulation-based comparison study with other optimization algorithms such as particle swarm optimization, differential evolution, and whale optimization algorithm.
In the paper "A Novel IR Analyzer Based Property Extraction for Segmented Branch Retinal Artery Occlusion and GWO-CNN Based Classification - An Ophthalmic Outcome," the authors examine the problem of Branch Retinal Artery Occlusion (BRAO), a disorder causing permanent loss of vision. The paper presents a classification framework for BRAO using neural networks. The main steps of noise reduction for fundus image quality improvement, adaptive clustering with super pixel segmentation and gray wolf optimization-based convolution neural network classification are discussed. The paper reports the performance accuracy of the method to draw inferences.
The paper, "Optimal Location of Static Var Compensator to Regulate Voltage in Power System," presents a method for determining the optimal location of shunt-connected Flexible AC Transmission Systems, such as Static Var Compensator (SVC) or Static Synchronous Compensator for regulating voltage levels of all buses. For this purpose, three indices viz. Voltage Drop Index (VDI), Total Voltage Drop Index (TVDI), and Total Voltage Drop of Network Index (TVDNI) are used. The paper presents simulation studies to show that the method can identify the optimal placement of SVC, and the compensation of voltage drop caused by increasing load. These studies are conducted for two scenarios: network loads increase with a constant coefficient and at random. The results are discussed to bring out the efficacy of the proposed method.
As an alternative antenna design for gain and bandwidth enhancement, the authors of "Alternatives to Metamaterial Based Antennas for Gain and Bandwidth Enhancement” present configurations of electromagnetically coupled microstrip antennas and arrays. A comparison is made between the configurations proposed in this paper and the metamaterial configurations reported in the literature. Inferences are drawn from the study regarding gain and bandwidth achieved with the proposed configurations compared to the metamaterial configurations in the same compact space.
Quality of service (QoS) parameters in Vehicular Ad hoc Networks (VANETs) are negatively impacted by the Link Breakage problem. In the paper "A Routing Technique for Enhancing the Quality of Service in Vanet," the authors present an approach that improves upon the relevant parameters and ensures continuous communication between the ends of a network. This is accomplished by selecting a possible Forwarding Vehicle, (FV) that will wait in the source's transmission zone until it receives the entire data packet. The paper presents details of the proposed method and its data-rate results.
In the paper "Synthesis of BSA-Conjugated ZnO Nanoparticle for Pb2+ Sensing Applications," the authors present a method for detecting extremely low concentrations of Lead ions using solution-processed Bovine Serum Albumin conjugated ZnO nanoparticle (BCZ) networks. The paper discusses the limit of detection obtained from a fabricated device.
The paper on "New Design of Binary to Ternary Converter" presents a binary-to-ternary converter. Binary QCA (bQCA) and ternary QCA (TQCA) need to communicate amongst themselves to be able to use TQCA devices. To accomplish this, the authors present make an interface design for a binary-to-ternary converter. The paper discusses the working of the converter through results of simulation study of the proposed circuit.
In the paper "SEEDDUP: A Three-Tier SEcurE Data DedUPlication Architecture-Based Storage and Retrieval for Cross-Domains Over Cloud," the authors present a three-tier secure data deduplication architecture (called SEEDDUP) for cloud-based data storage and retrieval. Along with data deduplication the architecture offers proper indexing and user privacy so that only legitimate users can request data for limited times and spurious data requests are not processed. Based on the file size and type, the Cuckoo Search Algorithm is used to determine the optimal chunk size. The paper presents the performance results of the architecture in terms of latency, throughput and deduplication achieved.
The paper on "Performance Evaluation of ILC Controller for Anesthesia Process" presents a method to regulate the depth of hypnosis during anesthesia through an Iterative Learning Controller (ILC) that uses the Brain Activity Index (BIS) as a feedback signal. A software model is used to design an automatic propofol infusion system, or the patient model wherein the anesthesia process is approximated to first-order time delay from the model transfer function. The paper reports the ILC controller’s performance in terms of quality indices, error indices, and Integral Absolute Error and compares with other method to draw inferences about the efficacy of the proposed method.
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 research rate the University of California, Santa Barbara, USA from 1994 to 1996 before joining IIT Delhi. His research interests are in digital signal processing, under water and air acoustics, human and machine speech communication, and multi-sensor data fusion. Professor Arun Kumar is an inventor on 10 granted US patents. He has guided 16 PhD theses and 180 Master’s theses. He has authored/co-authored 160 papers in peer reviewed journals and conferences. He has been project investigator/co-investigator for 72 funded R&D projects from industry and government. These projects have led to several technology and know-how transfers. Many of the technologies co-developed by him are deployed in the field and are in practical use. Professor Arun Kumar has served on several technical and organization committees of conferences, and on national level committees in electronics and defence fields. He is co-founder and director of a company that develop signal processing and AI based technologies and products for speech-based and multi-modal human and machine. He is currently deputy chief editor 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 2012-2016 and mentor deputy director (Strategy & Planning, International Affairs) at IIT Jammu from 2018-2021. He also served as the chairman of Astra Microwave Products Limited, Hyderabad from 2009-2019 and Dr R P Shenoy Astra Microwave chair professor at IIT Delhi from 2014-2019. His research interests include RF MEMS, high frequency wireless communication, microwave engineering, microwave passive and active circuits, device modelling, millimetre and sub-millimetre wave IC design, body area networks, flexible and wearable electronics, medical applications of sub-terahertz waves and reconfigurable microwave circuits including miniaturized antennas. He successfully completed 38 major sponsored projects, 52 consultancy projects and 61 technology development projects. He has authored/co-authored 601 research papers, 22 state-of-the art books, 4 book chapters and 2 e-books. He holds 26 patents, 6 copyrights and one trademark. He has guided 30 PhD thesis and more than 100 Master’s theses. He is a Life Fellow of IEEE and Fellow of INAE and IETE. He is the chief editor of IETE Journal of Research, associate editor of the International Journal of Microwave and Wireless Technologies, Cambridge University Press. He served as a Distinguished Microwave Lecturer of IEEE MTT-S for the period 2012-2014.
Recipient of numerous awards including IEEE MTT Society Distinguished Educator Award (2014); Teaching Excellence Award (2012) from IIT Delhi; Indian National Science Academy (INSA) Young Scientist Award (1986); Top Invention Award (1991) of the National Research Development Council for his contributions to the indigenous development of ferrite phase shifter technology; VASVIK Award (1994) for the development of Ka- band components and phase shifters; Ram Lal Wadhwa Gold Medal (1995) from the Institution of Electronics and Communication Engineers (IETE); Academic Excellence Award (1998) from Indian Government for his pioneering contributions to phase control modules for Rajendra Radar, Shri Om Prakash Bhasin Award (2009) in the field of Electronics and Information Technology, VASVIK Award (2012) for the contributions made to the area of Information, Communication Technology (ICT) and M N Saha Memorial Award (2013) from IETE. His name has recently figured in the Scopus Elsevier top 2% Scientists under the Category “Year 2021”.Email: [email protected]
Ranjan K Mallik
Ranjan K Mallik (FIETE, FIEEE, FIET, FTWAS, FNAE, FNA, FNASc, FASc) is an Institute chair professor in the Department of Electrical Engineering, Indian Institute of Technology (IIT) Delhi. He received the BTech degree from IIT Kanpur and the MS and PhD degrees from the University of Southern California, Los Angeles, all in electrical engineering. He has worked as a scientist in the Defence Electronics Research Laboratory, Hyderabad, India, and as a faculty member in IIT Kharagpur and IIT Guwahati. His research interests are in diversity combining and channel modelling for wireless communications, space-time systems, cooperative communications, multiple-access systems, power line communications, molecular communications, difference equations, and linear algebra. He is a recipient of the Shanti Swarup Bhatnagar Prize, the Hari Om Ashram Preriot Dr Vikram Sarabhai Research Award, the Khosla National Award, the IETE Ram Lal Wadhwa Award, the IEI-IEEE Award for Engineering Excellence and the J C Bose Fellowship. He is a member of Eta Kappa Nu and a Fellow of IEEE, the Indian National Academies INAE, INSA, NASI, and IASc, TWAS, the West Bengal Academy of Science and Technology, IET (UK), IETE (India), The Institution of Engineers (India) and the Asia-Pacific Artificial Intelligence Association. He served as an area editor and an editor for the IEEE Transactions on Wireless Communications, and as an editor for the IEEE Transactions on Communications. He was a Technical Program Committee (TPC) co-chair for the Wireless Communications Symposium of IEEE GLOBECOM 2008 and IEEE ICC 2010, a TPC co-chair for the PHY Track of IEEE WCNC 2013, and a TPC co-chair for the Communication Theory Symposium of IEEE ICC 2021. He is currently deputy chief editor of IETE Journal of Research.Email: [email protected]