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A Novel Approach for State of Health Estimation and Remaining Useful Life Prediction of Supercapacitors Using an Improved Honey Badger Algorithm Assisted Hybrid Neural Network

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Protection and Control of Modern Power Systems 2024年第6期9卷 1-18页

作者： Zhenxiao Yi Shi Wang Zhaoting Li Licheng Wang Kai Wang the School of Electrical Engineering Qingdao UniversityQingdao 266071Chinaand the State Key Laboratory of Reliability and Intelligence of Electrical EquipmentHebei University of TechnologyTianjin 300130China the Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China the School of Engineering Brown UniversityProvidenceRhode Island 02912USA the School of Information Engineering Zhejiang University of TechnologyHangzhou 310014China the School of Electrical Engineering Qingdao UniversityQingdao 266071China

Supercapacitors(SCs)are widely recognized as excellent clean energy storage *** state of health(SOH)estimation and remaining useful life(RUL)prediction are essential for ensuring their safe and reliable *** paper introduces a novel method for SOH estimation and RUL prediction,based on a hybrid neural network optimized by an improved honey badger algorithm(HBA).The method combines the advantages of convolutional neural network(CNN)and bidirectional long-short-term memory(BiLSTM)neural *** HBA optimizes the hyperparameters of the hybrid neural *** CNN automatically extracts deep features from time series data and reduces dimensionality,which are then used as input for the ***,recurrent dropout is introduced in the recurrent layer to reduce overfitting and facilitate the learning *** approach not only improves the accuracy of estimates and forecasts but also significantly reduces data processing *** under different working conditions are used to validate the proposed *** results show that the proposed hybrid model effectively extracts features,enriches local details,and enhances global perception *** proposed hybrid model outperforms single models,reducing the root mean square error to below 1%,and offers higher prediction accuracy and robustness compared to other methods.

关键词： Supercapacitors state of health remaining useful life honey badger algorithm recurrent dropout.

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On the Performance of Rate-Splitting Multiple Access in Coordinated Direct and Relay Transmission 17

On the Performance of Rate-Splitting Multiple Access in Coor...

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17th IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2023

作者： Kumari, Supriya Srirangarajan, Seshan Bhatia, Vimal Indian Institute of Technology Delhi Bharti School of Telecommunication Technology and Management India Indian Institute of Technology Delhi Department of Electrical Engineering India Indian Institute of Technology Indore Department of Electrical Engineering India

ISBN: (纸本)9798350307672

This paper introduces rate splitting multiple access (RSMA) in coordinated direct and relay transmission (CDRT) to improve spectrum efficiency and system performance. In the proposed system, a base station (BS) communicates directly with user equipment 1 (UE1) and through decode and forward (DF) relay with user equipment 2 (UE2). Here, the DF relay works in half-duplex relaying (HDR) mode. A passive intelligent reflecting surface (IRS) is synergistically combined with a DF relay called the hybrid relay network (HRN) to provide beneficial multipath diversity. We hereby derive the analytical expressions of outage probability and ergodic capacity of the HRN system. Asymptotic analysis of outage probability is also done. Through simulation results, the analytical expressions derived are verified. © 2023 IEEE.

关键词： Asymptotic analysis

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Wireless Power Transfer to Electric Vehicles along with Regenerative Braking using battery-supercapacitor combination

Wireless Power Transfer to Electric Vehicles along with Rege...

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2022 IEEE International Conference on "Power Electronics, Smart Grid, and Renewable Energy", PESGRE 2022

作者： Sai Sushma, P. Tummuru, Narsa Reddy Misra, Himanshu School of Computing and Electrical Engineering Indian Institute of Technology Kamand Mandi India

ISBN: (纸本)9781665448376

Wireless power transfer (WPT) has gotten a lot of attention in the present times and is going to become our potential future. From small power application scenarios such as charging a mobile phone to high power scenarios like charging an electric vehicle (EV), WPT is investigated as an option. The growing market share of electric vehicles raises questions whether it is possible to integrate wireless charging technology developed for low power applications into this high-power application. Furthermore, it should be investigated if the integration of regenerative braking into the overall system is possible. Several converters have been proposed to enable regenerative braking (RB). However, there is a lack of studies examining the interaction of both technologies on the system level. This paper proposes the integration of an inductive wireless power transfer (IWPT) system and a regenerative braking system into an EV. The merits of the proposed system are represented in scenarios where a considerable amount of power is lost due to frequent acceleration and deceleration. This paper describes the study of the system level integration of a regenerative braking system and a WPT system into an EV. It presents the design, development, and simulation of the complete system along with the brushless direct current (BLDC) traction motor. It shows the simulation model of the Inductive wireless power transfer system (two stage) to EV and acceleration/deceleration phenomenon of BLDC motor. The speed and torque parameters of BLDC motor are the externally controlling variables of EV, having battery-supercapacitor (battery-SC) as storage devices during this transition period. Regenerative braking in BLDC motor can be observed when EV is under sudden deceleration motions consuming/producing excessive current where SC picks up the transients in place of the battery. © 2022 IEEE

关键词： Energy transfer

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Silk-Aloe Vera Composite Piezoelectric Film: A New Paradigm in Eco- Friendly Piezoelectrics

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible Electronics 2024年第7期3卷 292-299页

作者： Bhagavathi, K. Aditya Bonam, Satish Joseph, Jose Rao, Karri Trinadha Singh, Shiv Govind Vanjari, Siva Rama Krishna Indian Institute of Technology Hyderabad Department of Electrical Engineering Hyderabad502285 India Digital University Kerala School of Electronic Systems and Automation Trivandrum695317 India

Piezoelectric materials derived from biological sources are given greater consideration in the present era due to their advantages, such as biocompatibility, sustainability, and potential for tailoring properties through chemical modification and genetic engineering. Silk, a bio-piezopolymer, derived from the silk glands of various species of silkworms, is extensively studied for its piezoelectric properties and applications thereof. This article presents the development of a composite bio-piezopolymer, amalgamating the material properties of silk and the extracts taken from a tropical desert plant, aloe vera. A comprehensive material characterization protocol is embraced to assess the performance of the thin film formed from the silk-aloe vera (SAV) composite solution. In addition to an improvement in the piezoelectric characteristics, the composite film exhibited excellent surface uniformity and crystallinity, proving its potential for real-time applications. Pressure sensors were fabricated with SAV composite films and characterized using a custom-built test setup. The characterization results surpassed the performance achieved by pressure sensors fabricated using only silk thin film. © 2022 IEEE.

关键词： Pressure sensors

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CRIS-b: A High-Speed Unified Modulo Reduction Algorithm and Hardware Architecture for CRYSTALS-Kyber

CRIS-b: A High-Speed Unified Modulo Reduction Algorithm and ...

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International Conference on VLSI Design

作者： Alip Majumdar Rahul Shrestha School of Computing and Electrical Engineering Indian Institute of Technology Mandi

ISBN: (数字)9798331522445

ISBN: (纸本)9798331522452

This paper presents highly reliable algorithm and high-speed hardware architecture for a unified modulo reduction for CRYSTALS-Kyber. This new architecture for modulo reduction is capable of operating at a maximum clock frequency of 351.62 MHz on Artix-7 FPGA platform, consuming a latency of 5 clock cycles, which is approximately 35.24% faster than state-of-the-art implementations. In this work, we have alleviated the size expansion problem of intermediate value of the conventional Barrett algorithm (which is one of the fastest and most reliable algorithm for modulo reduction, reported in literature) by suggesting a new technique, referred as “Conditional $R$ -index Switching for $b$ -value Minimization (CRIS-b)”. We propose a unified modulo reduction design handling both positive and negative spectrum numbers for all arithmetic modulo operations in a butterfly unit of Number Theoretic Transform(NTT).

关键词： Accuracy Switches Very large scale integration Reliability theory Approximation algorithms Minimization Hardware Quantum cryptography Clocks Arithmetic

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Machine learning empowered UAV-based beamforming design in ISAC systems

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Science China(Information Sciences) 2025年第5期68卷 285-286页

作者： Xiangyang DUAN Xiaoqi ZHANG Shuqiang XIA Zhongbin WANG Yihua MA Weijie YUAN State Key Laboratory of Mobile Network and Mobile Multimedia Technology Wireless and Computing Research InstituteZTE Corporation School of Electrical and Data Engineering University of Technology Sydney School of Automation and Intelligent Manufacturing Southern University of Science and Technology

Integrated sensing and communication (ISAC) has been proposed as an enabling technology for the realization of the next-generation wireless system,which focuses on performing wireless communication and sensing *** the various potential ISAC-based applications,unmanned aerial vehicle (UAV)-based ISAC plays a significant part in unlocking the potential of future next-generation wireless communication,facilitating low-latency data transmission in high-mobility *** by recent advancements,a variety of effective techniques have been investigated to optimize beamforming design in ISAC *** instance,the authors in [1] introduced an extended Kalman filtering (EKF)-based method tailored for millimeter wave (mmWave) ISAC ***,Ref.[2]proposed an extended interacting multiple model (IMM)-EKF framework designed for vehicular networks with intricate roadway *** these advancements,the aforementioned methods typically employ a separate scheme for channel prediction and beam alignment,which introduces additional signaling overhead in real-world ***,there is a demand for an end-to-end beamforming design approach specifically for UAV-based ISAC systems.

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WISER: Weak Supervision and Supervised Representation Learning to Improve Drug Response Prediction in Cancer 41

WISER: Weak Supervision and Supervised Representation Learni...

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41st International Conference on Machine Learning, ICML 2024

作者： Shubham, Kumar Jayagopal, Aishwarya Danish, Syed Mohammed Prathosh, A.P. Rajan, Vaibhav Department of Electrical Communication Engineering Indian Institute of Science Karnataka Bengaluru India Department of Information Systems and Analytics School of Computing National University of Singapore Singapore Indian Institute of Technology Bihar Patna India

Cancer, a leading cause of death globally, occurs due to genomic changes and manifests heterogeneously across patients. To advance research on personalized treatment strategies, the effectiveness of various drugs on cells derived from cancers (‘cell lines') is experimentally determined in laboratory settings. Nevertheless, variations in the distribution of genomic data and drug responses between cell lines and humans arise due to biological and environmental differences. Moreover, while genomic profiles of many cancer patients are readily available, the scarcity of corresponding drug response data limits the ability to train machine learning models that can predict drug response in patients effectively. Recent cancer drug response prediction methods have largely followed the paradigm of unsupervised domain-invariant representation learning followed by a downstream drug response classification step. Introducing supervision in both stages is challenging due to heterogeneous patient response to drugs and limited drug response data. This paper addresses these challenges through a novel representation learning method in the first phase and weak supervision in the second. Experimental results on real patient data demonstrate the efficacy of our method WISER (Weak supervISion and supErvised Representation learning) over state-of-the-art alternatives on predicting personalized drug response. Our implementation is available at https://***/kyrs/WISER. Copyright 2024 by the author(s)

关键词： Self-supervised learning

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Age-of-information minimization for energy harvesting sensor in non-stationary environment 21

Age-of-information minimization for energy harvesting sensor...

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21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2023

作者： Jaiswal, Akanksha Chattopadhyay, Arpan The Department of Electrical Engineering Indian Institute of Technology Delhi India The Department of Electrical Engineering The Bharti School of Telecom Technology and Management Indian Institute of Technology Delhi India

ISBN: (纸本)9783903176553

In this paper, we consider age-of-information (AoI) minimization for an energy harvesting (EH) source that samples and sends the observations to a sink node. At each time, the source observes the channel quality, the available energy, and the age, and decides whether to sample and send the observation to the sink. We formulate the problem as a Markov decision process (MDP) and establish a threshold structure for the optimal sampling policy. Next, motivated by the popular sliding window upper confidence bound reinforcement learning (SWUCRL2) algorithm for non-stationary reinforcement learning (RL), we leverage this threshold structure and propose an age-energy-channel based SW-UCRL2 (AEC-SW-UCRL2) algorithm to handle unknown and time-varying energy harvesting rate and channel statistics, when an upper bound to the total variation of each of these quantities over the time horizon is available. Next, for the case when these variation budgets are not available, motivated by the popular bandit-over-RL (BORL) algorithm, we propose an algorithm named age-energy-channel based bandit-over-reinforcement learning (AEC-BORL). Finally, we demonstrate the superior numerical performance of these proposed algorithms via numerical experiments. © 2023 IFIP.

关键词： Reinforcement learning

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Tomato leaf disease detection using series of Convolutional and Depthwise Convolutional Layers

Tomato leaf disease detection using series of Convolutional ...

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2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2023

作者： Deb, Sagar Deep Kashyap, Rachit Abhishek, Arjun Lavanya, R. Paritosh, Pushp Jha, Rajib Kumar Indian Institute of Technology Patna Department of Electrical Engineering Patna India Indian Institute of Technology Patna Department of Electrical Engineering Bihar India SRM Institute of Science and Technology Department of Computing Technologies Chennai India

ISBN: (纸本)9798350312126

Numerous studies have focused on enhancing the effectiveness of identifying leaf diseases through image classification. However, it is essential to develop a classification system with fewer parameters to enable it to operate efficiently on mobile devices. As a result, A lot of research works are going on to make the neural network computationally light so that we can utilise these networks on a mobile device as it cannot afford a GPU to run in background because of the space and memory limitations of a portable device. In this study, we propose a deep learningbased approach for tomato leaf disease detection using a series of convolutional and depthwise convolutional layers. The proposed model contains only 17,209 trainable parameters. The model was able to achieve high accuracy of 92.10 % on tomato crop from a publicly available PlantVillage dataset while utilizing a smaller number of parameters. © 2023 IEEE.

关键词： Graphics processing unit

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Energy-Preserving Indirect-feedback for Wireless Power Transfer: Algorithm & Hardware Architecture

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2025年

作者： Sarma, Siddhartha Shrestha, Rahul Chaurasiya, Rohit B. Indian Institute of Technology School of Computing and Electrical Engineering Mandi175005 India Indian Institute of Technology Jammu181221 India

Recognising the limitations of existing channel-estimation schemes for energy beamforming, this paper proposes an energy-preserving, indirect-feedback based approach to determine the optimal energy beamforming vector, specially designed for battery-free RF energy harvesting devices. Upon elaborating on the key ideas behind the proposed approach—dynamics of the harvest-then-transmit protocol, non-linearity of harvesting efficiency and the latency associated with the charging process—we present an algorithm and its hardware architecture to concretise the proposed approach. The developed algorithm is supplemented by mathematical analysis and numerical simulations. Furthermore, the designed hardware architecture has been post-route implemented on an FPGA platform, and ASIC post-layout simulated in 90 nm-CMOS technology node. For the configuration in the numerical results section, a low-power sensor node operating at the milliwatt level can save approximately 1 mJ of energy by adopting the proposed scheme, enabling the transmission of 5 additional ***, the saved energy—and consequently, the number of additional packets—scales linearly with the number of transmit antennas. © 2025 IEEE. All rights reserved.

关键词： Field programmable gate arrays (FPGA)

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