Indian Institute of Technology Palakkad&nbsp;(IIT Palakkad or IIT PKD) is a public autonomous&nbsp;engineering&nbsp;and&nbsp;research&nbsp;institute located in&nbsp;Palakkad,&nbsp;Kerala. It was&nbsp;one of the five new&nbsp;IITs&nbsp;proposed in the&nbsp;2014 Union budget of India. The campus was inaugurated on 3 August 2015. The institute has 94 faculty, 978 students, and 63 non-teaching staffs.

IT Palakkad currently offers four-year Bachelor of Technology (B.Tech) and two years MS programmes in 8 different engineering disciplines including&nbsp;Computer Science, Electrical, Mechanical, Civil among others.

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IIT Palakkad

An aperture coupled feeding technique based dual band high gain 4 × 4 microstrip antenna array has been presented here for X-band radar and satellite communication. The designed array consists of three layers which are corporate feed network, 2D array of radiating patches, and coupling apertures on the ground plane. The novelty of the work is the designing of a new asymmetric H-shaped slot for the aperture coupled antenna (ACA) element. The antenna exhibits dual resonances in X-band at frequencies 8.45 and 11.15 GHz, those are altered by changing ACA's physical dimensions. The three layers of the array are printed on two Taconic TLY-5 dielectric materials, which are stacked over each other. The designed array is realized on overall size of 100×100×2.09 mm3 and having return loss bandwidth (BW) of 3.2 % in both bands that covers frequencies 8.53 to 8.81 GHz and 10.8 to 11.15 GHz. In two bands array radiates with gain of 17.1 and 19.34 dBi, and efficiencies of 90.7 % and 94.1 % respectively. The array exhibits considerable low cross-polarization of < - 14.2 dB and <- 36.2 dB at two operating frequencies. © 2023 IEEE.

Department of Electrical Engineering

World University root node

International Conference on Microwave, Antenna and Communication, MAC 2023

Novel Dual Band High Gain Antenna Array Using Aperture Coupled Feeding for X-Band Radar

Energy generation is stepping on to the integration of more renewable sources as it is environment friendly and poses less ecological impact. Practical feasibility of such technologies has to be studied well before it is implemented on a system. Large scale integration of Renewable Energy Sources (RES) will reduce the total system inertia and can have adverse effects on power system transient stability. The objective of this paper is to find the impact of renewable energy penetration on one of the power system stability indicators called critical clearing time (CCT). The study is carried out on the well known IEEE 9 bus system considering different penetration of type-IV wind turbine generators (WTG). CCT is calculated for different fault locations using Dynamic Security Assessment Tools (DSA Tools) software of Powertech Labs. Furthermore, the correlation between inertia distribution index (IDI) and CCT is also explored. The results shows that the RES can have positive as well as negative impact on CCT. © 2023 IEEE.

5th International Conference on Power, Control and Embedded Systems, ICPCES 2023

Critical Clearing Time Revisited in an Inverter Dominated Power Systems

For a convolutional code in the presence of a symbol erasure channel, the information debt I(t) at time t provides a measure of the number of additional code symbols required to recover all message symbols up to time t. Information-debt-optimal streaming (iDOS) codes are convolutional codes which allow for the recovery of all message symbols up to t whenever I(t) turns zero under the following conditions; (i) information debt can be non-zero for at most t consecutive time slots and (ii) information debt never increases beyond a particular threshold. The existence of periodically-time-varying iDOS codes are known for all parameters. In this paper, we address the problem of constructing explicit, time-invariant iDOS codes. We present an explicit time-invariant construction of iDOS codes for the unit memory (m = 1) case. It is also shown that a construction method for convolutional codes due to Almeida et al. leads to explicit time-invariant iDOS codes for all parameters. However, this general construction requires a larger field size than the first construction for the m = 1 case. © 2023 IEEE.

Department of Data Science

IEEE International Symposium on Information Theory - Proceedings

Explicit Information-Debt-Optimal Streaming Codes With Small Memory

Flexible power point tracking (FPPT) control algorithms have been introduced in the literature to provide frequency support in low-inertia grid-connected photovoltaic (PV) systems. This is achieved by regulating the PV output power to a power reference obtained from the energy management system. Partial shading of PV arrays is a frequent phenomena that needs to be investigated for FPPT operation of PV systems. This paper proposes a simple and improved secant-based global FPPT algorithm that tracks the power reference during partial shading conditions. Guaranteed and fast convergence with flexibility to operate on both sides of the global maximum power point are the main contributions of the proposed algorithm. Experimental validation is carried out to demonstrate the efficacy of the proposed algorithm. IEEE

IEEE Transactions on Power Electronics

Improved Secant-Based Global Flexible Power Point Tracking in Photovoltaic Systems Under Partial Shading Conditions

In ultrasound (US)-guided interventions, accurately tracking and visualizing needles during in-plane insertions are significant challenges due to strong directional specular reflections. These reflections violate the geometrical delay and apodization estimations in the conventional delay and sum beamforming (DASB) degrading the visualization of needles. This study proposes a novel reflection tuned apodization (RTA) to address this issue and facilitate needle enhancement through DASB. The method leverages both temporal and angular information derived from the Radon transforms of the radio frequency (RF) data from plane-wave imaging to filter the specular reflections from the needle and their directivity. The directivity information is translated into apodization center maps through time-to-space mapping in the Radon domain, which is subsequently integrated into DASB. We assess the influence of needle angulations, projection angles in the Radon transform, needle gauge sizes, and the presence of multiple specular interfaces on the approach. The analysis shows that the method surpasses conventional DASB in enhancing the image quality of needle interfaces while preserving the diffuse scattering from the surrounding tissues without significant computational overhead. The work offers promising prospects for improved outcomes in US-guided interventions and better insights into characterizing US reflections with Radon transforms.

IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL

Enhanced Needle Visualization With Reflection Tuned Apodization Based on the Radon Transform for Ultrasound Imaging

Anti-aliased Convolutional Neural Networks (CNNs) have been proposed to overcome the shift variant nature of the CNNs. The fundamental building block of the anti-aliased CNN has been the application of Gaussian or wavelet-based smoothing before the pooling operation. However, in all these approaches, the feature maps' edges are also smoothed while suppressing high-frequency components. In this work, two novel pooling approaches are presented, namely the Laplacian-Gaussian Concatenation with Attention (LGCA) pooling and Wavelet-based Approximate-Detailed Coefficient concatenation with Attention (WADCA) that can preserve the edges in the feature maps. The results suggest that the proposed pooling approaches outperform conventional as well as blur pooling for classification, segmentation and auto-encoders. In terms of average binary classification accuracy (cats vs dogs), the proposed LGCA approach outperforms the conventional pooling and blur pooling by 4\% and 2\%, 3\% and 4\%, 3\% and 0.5\% for MobileNetv2, DenseNet121 and ResNet50 respectively. On the other hand, the proposed WADCA approach outperforms the normal pooling and blur pooling by 5\% and 3\%, 2\% and 3\%, 2\% and 0.17\% for MobileNetv2, DenseNet121 and ResNet50 respectively. It is also observed from the results that edge-preserving pooling does not have any significance in segmentation tasks possibly due to high to low-resolution translation. Meanwhile, high-resolution reconstruction has been observed for the LGCA pooling in the case of convolutional auto-encoders.

MULTIMEDIA SYSTEMS

Edge preserved universal pooling: novel strategies for pooling in convolutional neural networks

In the recent past, with the rapid surge of COVID-19 infections, lung ultrasound has emerged as a fast and powerful diagnostic tool particularly for continuous and periodic monitoring of the lung. There have been many attempts towards severity classification, segmentation and detection of key landmarks in the lung. Leveraging the progress, an automated lung ultrasound video analysis package is presented in this work, which can provide summary of key frames in the video, flagging of the key frames with lung infection and options to automatically detect and segment the lung landmarks. The integrated package is implemented as an open-source web application and available in the link https://github.com/anitoanto/alus-package.\& COPY; 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

SOFTWAREX

SPAALUV: Software Package for Automated Analysis of Lung Ultrasound Videos

The clinical interpretability of specular interfaces in ultrasound (US) imaging is heavily influenced by the anatomical knowledge of the operator and the transmit-receive beamforming employed for imaging. The violation of the conventional diffuse assumptions by highly directive specular reflections makes their detection challenging which increases the cognitive burden of operators in tissue characterization or calibrating the beam steering/transducer to ensure their detection. However, the areas for improved operator assistance and related workflow in this regard remain largely unexplored. This work proposes a novel method called tiered subaperture (SA) directivity indexing, which employs a SA-level measurement of energy in the reflections through multiangle plane wave transmissions to automatically identify the directivity of specular reflections. The reflection directivity is vectorized and visually fed as a characterized colored image to the operator to distinguish the specular patterns in the US data. The technique is illustrated for clinical use cases such as needle tracking in guided interventional procedures, anisotropy in MSK US, and bone fracture monitoring. The proposed method improves retention, enables freehand scans, and augmentation of hand-eye coordination for the operators for tissue characterization, beamforming, and transducer calibration thus aiding quicker diagnosis by saving procedure times.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

A Novel Technique for Estimation and Detection of Specular Reflections Leveraging High Frame Rate Ultrasound Imaging

In the recent years, deep learning techniques have received a great attention in a wide range of practical problems, including the event detection, localization, classification, and prediction. In this paper, we present a real-time bidirectional long-short term memory (BiLSTM) based human presence sensing using the WiFi channel state information (CSI) feature for non-intrusive occupancy detection systems in indoor environments by selecting best hyper-parameters. In this study, we created real-time Wi-Fi enabled Raspberry Pi computing platform to collect CSI datasets for training and testing purposes by considering different room sizes, fixed objects and different activities. On the wide variety of CSI datasets, evaluation results showed that the proposed magnitude CSI-BiLSTM based human presence detection (HPD) method had an average sensitivity (SE) of 92.23 %, specificity (SP) of 91.18 % and accuracy (ACC) of 91.68% for the 20% test CSI segments taken from the same training dataset and had an average SE of 85.71 %, SP of 91.59% and ACC of 88.67% on the unseen CSI dataset collected under different room conditions. In real-time Raspberry Pi testing environment, the proposed method had an average SE of 99.35%, SP of 94.39 % and ACC of 97.00 %. The proposed magnitude CSI-BiLSTM based HPD method had an average computational time of 1.37 ms with a model size of 509.67 kB. © 2023 IEEE.

2nd International Conference on Microwave, Optical and Communication Engineering, ICMOCE 2023

Bidirectional LSTM based Sequence Classification Approach for Human Presence Detection using Channel State Information

Photoplethysmogram (PPG) is a noninvasive technique to estimate heart rate and respiration rate with advantages over electrocardiogram (ECG) in terms of ease of sensing. In the realm of energy-efficient health monitoring, compressive sensing (CS) is gaining prominence, particularly for signals that exhibit sparsity. This study explores to find the best sparse recovery algorithm for a fixed sparsifying matrix including impulse (I), discrete cosine (C), discrete sine (S) [I C S] and deterministic binary block diagonal (DBBD) sensing matrix for the reconstruction of the CS PPG signal, with a focus on quality metrics and potential very large scale integration (VLSI) implementations. At a compression ratio (CR) of 3, the orthogonal matching pursuit (OMP) algorithm, DBBD and [I C S] combination outperform other recovery algorithms, achieving an average percentage root mean square difference (PRD) of 1.86%, maximum absolute error (MaxAE) of 0.0976 and signal-to-noise ratio (SNR) of 36.07 dB. However, as CR increases, the approximate message passing (AMP) algorithm, DBBD and [I C S] combination often surpass OMP, achieving an average PRD value of 9.79% at a CR of 5. Additionally, AMP is computationally simpler than OMP for lower CRs. Although OMP is recommended for its accuracy across various CRs, AMP often matches or even outperforms it at higher CRs with the fixed combination of DBBD and [I C S] in compressed PPG signal recovery. The results emphasize the importance of finding suitable sparse recovery algorithms for specific CRs, sparsifying matrices, sensing matrices and the trade-offs between compression, distortion and complexity. © 2023 IEEE.