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1st International Conference on Innovative engineering Sciences and Technological research, ICIESTR 2024

作者： Kannabiran, Kanimozhi Mohamed Rabi, B. Raja Jayapalan, Booma Krismadinata Lakshmanan, Thangapalani Rajalakshmi, K. Npr College of Engineering & Technology Dept. of Electrical and Electronics Engg. Natham India Dept. of Mechanical Engineering Rathinam Technical Campus Coimbatore India Psna College of Engineering and Technology Dept. of Electronics and Communication Engg. Dindigul India Universitas Negeri Centre for Energy and Power Electronics Research Pedang Indonesia Sri Sairam Institute of Technology Dept. of Computer Science and Engineering Chennai India Npr College of Engineering & Technology Dept. of Computer Science and Engineering Natham India

ISBN: (纸本)9798350348637

Stability of power electronic converters is one of the most important problems related to their dynamics. The problems related to global asymptotic stability is discussed here. The design example used is DC-DC buck converter with Adaptive sliding mode control. An averaged small signal model is derived and transfer functions are obtained. Stability is also verified using conventional techniques by MATLAB simulation. Simulation results and mathematical proof shows that closed loop system designed is stable and a fast response is obtained. Simulated results show that the simulated converter system acquires the excellent robustness feature of achieving a stable steady-state and fast transient response under variable operating points. A prototype model has been developed and simulated results are compared with experimental results. The results validate the stability analysis of Dc-Dc buck converter © 2024 IEEE.

关键词： Buck converter

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Controlled Dropout for Uncertainty Estimation

Controlled Dropout for Uncertainty Estimation

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Hasan, Mehedi Hossain, Ibrahim Rahman, Ashikur Nahavandi, Saeid Institute for Intelligent Systems Research and Innovation Deakin University GeelongVIC3220 Australia Bangladesh University of Engineering and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350337020

Uncertainty quantification in a neural network is one of the most discussed topics for safety-critical applications. Though Neural Networks (NNs) have achieved state-of-the-art performance for many applications, they still provide unreliable point predictions, which lack information about uncertainty estimates. Among various methods to enable neural networks to estimate uncertainty, Monte Carlo (MC) dropout has gained much popularity in a short period due to its simplicity. In this study, we present a new version of the traditional dropout layer where we are able to fix the number of dropout configurations. As such, each layer can take and apply the new dropout layer in the MC method to quantify the uncertainty associated with NN predictions. We conduct experiments on both toy and realistic datasets and compare the results with the MC method using the traditional dropout layer. Performance analysis utilizing uncertainty evaluation metrics corroborates that our dropout layer offers better performance in most cases. © 2023 IEEE.

关键词： dropout Monte Carlo dropout neural network Uncertainty estimation

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ECDSA-based tamper detection in medical data using a watermarking technique

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International Journal of Cognitive Computing in engineering 2024年第1期5卷 78-87页

作者： Ch, Rupa Vivek K, Naga Srivastava, Gautam Reddy Gadekallu Department CSE VR Siddhartha Engineering College Andhra Pradesh Vijayawada520 007 India Dept of Math and Computer Science Brandon University MB Canada Dept. of Computer Science and Math Lebanese American University Beirut1102 Lebanon Centre of Research Impact and Outcome Chitkara University Institute of Engineering and Technology Chitkara Punjab Rajpura140401 India Lebanese American University Department of Electrical and Computer Engineering Byblos Lebanon Lovely Professional University Division of Research and development Phagwara India Jiaxing University College of Information Science and Engineering Jiaxing China

Telemedicine is a form of healthcare delivery that employs communication technology to provide medical care to patients remotely. The use of telemedicine has seen a significant increase in recent years, presenting challenges such as patient privacy, data security, the need for reliable communication technology, and the potential for misdiagnosis without a physical examination. Digital Watermarking can assist in addressing such issues by incorporating a unique identifier into an image that can be used to authenticate its validity. To tackle these issues, this study proposes a robust digital watermarking approach tailored to brain medical images, combining hashing, the Elliptic Curve Digital Signature Algorithm (ECDSA), and the Integer Wavelet Transform-Discrete Cosine Transform (IWT-DCT). This method utilizes the Secure Hash Algorithm (SHA-256) to first segment the brain's Region of Interest (RoI). Subsequently, the hashed RoI, along with an ECDSA signature, is embedded into the high-frequency sub-bands of the medical image using IWT-DCT. The embedding process strategically alters the coefficients of the high-frequency sub-bands to accommodate the signature while minimizing perceptual distortion. The technique leverages the robustness of transformed-domain image watermarking techniques against various attacks and combines it with SHA-256 for integrity and ECDSA for authentication purposes. The results demonstrate that the suggested approach is robust to a variety of image processing techniques, including noise addition, filtering, and compression while maintaining high levels of imperceptibility. Key metrics such as the Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), and Structural Similarity Index (SSIM) were used to evaluate performance. The suggested strategy exhibited a substantial improvement over existing methods. The PSNR increased to 68.67, indicating higher image quality, while the MSE reduced to 0.96, demonstrating closer pixel values to the or

关键词： Mean square error

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Read Voltage Dependency of Random Telegraph Noise in the Intermediate State of TaOx-based ReRAM

Read Voltage Dependency of Random Telegraph Noise in the Int...

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2025 IEEE International Reliability Physics Symposium, IRPS 2025

作者： Yamauchi, Kenshin Misawa, Naoko Shima, Hisashi Naitoh, Yasuhisa Akinaga, Hiroyuki Matsui, Chihiro Takeuchi, Ken The University of Tokyo Dept. of Electrical Engineering and Information Systems Tokyo Japan Device Technology Research Institute National Institute of Advanced Industrial Science and Technology Ibaraki Japan

ISBN: (纸本)9798331504779

This work investigates random telegraph noise (RTN) behavior in the intermediate resistance states of 40nm TaOx-based analog ReRAM. Uniquely in the intermediate resistance states, both the frequency and amplitude of RTN fluctuations tend to increase with the read voltage. Considering the trade-off between increasing them and enhancing margins among adjacent resistance states as read voltage rises, a 0.2V readout minimizes RTN-induced misdetection of resistance states, achieving a significantly low error rate of 0.19%. © 2025 IEEE.

关键词： Fluctuation Pattern Classifier Multi-Level Cell Random Telegraph Noise ReRAM

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Synchrosqueezed Wavelet transform Based Power Quality Disturbance Detection and Monitoring of Solar Integrated Micro-Grid 2

Synchrosqueezed Wavelet transform Based Power Quality Distur...

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2nd International Conference on Power Electronics and Energy, ICPEE 2023

作者： Pattanaik, Debasish Swain, Sarat Chandra Samanta, Indu Sekhar Rout, Ullash Kumar Dash, Ritesh Swain, Kunjabihari Kiit Deemed to Be University School of Electrical Engineering Bhubaneswar India Iter Soa University Dept.of Computer Science and Engineering Bhubaneswar India Odisha University of Technology and Research Dept. of Electrical Engineering Bhubaneswar India Reva University Dept.of Electrical and Electronics Engineering Bangalore India Nist Institute of Science and Technology Dept. of Electrical and Electronics Engineering Berhampur India

ISBN: (纸本)9781665470582

Microgrid monitoring has gained popularity in recent years, owing to their popularity and the power quality disturbances (PQD) caused by renewable energies. Many artificial intelligence-based PQD monitoring strategies have been proposed by researchers. This paper presents a novel method for detecting, classifying and monitoring the power quality disturbances in solar integrated microgrids. Power quality events are detected by analysing the frequency signal with the wavelet synchro-squeezing transform (WSST). The features of power quality disturbances are used to classify them. For PQD classification, the retrieved features are fed into a Convolutional neural network (CNN) classifier, using GoogLeNet and SqueezeNetfier. Thus the accuracy was found to be 99.90% and 93.76% respectively. © 2023 IEEE.

关键词： Artificial Neural Network Convolutional Neural Network GoogLeNet neural network Innovation Micro Grid Power Quality Disturbances Renewable Energy Sources Wavelet synchro-squeezing transform

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A New Robust Hybrid Active Noise Control System 8

A New Robust Hybrid Active Noise Control System

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8th International Conference on Signal and Image Processing, ICSIP 2023

作者： Wang, Z. Xiao, Y. Ma, Y. Ma, L. Khorasani, K. Prefectural University of Hiroshima Dept. of Management & Information Systems Hiroshima734-8558 Japan Institute of Automation Jiangnan University Wuxi214122 China Concordia University Dept. of Electrical & Computer Engineering Montreal Canada

ISBN: (纸本)9798350397932

The conventional hybrid active noise control (ANC, HANC) may significantly degrade if the reference signal for the feedforward ANC (FFANC) subcontroller consists of not only a broadband component but also a low-frequency sinusoidal component that is uncorrelated or partially correlated with the narrowband noise component that is attenuated by the feedback ANC (FBANC) subcontroller. In this paper, a new robust HANC system is proposed to mitigate the performance degradation resulting from the low-frequency sinusoidal component. A band-pass filter bank (BPFB) is applied to the FFANC reference signal to separate the low-frequency sinusoidal component from the broadband one and each of them is fed to an FFANC subcontroller that solely focuses on a single noise component. A supporting filter takes the extracted broadband component and the residual error as its input and desired signal, respectively. The same BPFB is then applied to the supporting filter error in order to separate the remaining low-frequency sinusoidal component from the narrowband component that persists in the residual error. The use of the two BPFBs and the supporting filter allows the three HANC subcontrollers to operate practically independently, each taking care of one of the pre-processed noise components which are uncorrelated with each other irrespective of the relationship between the two original noise sources. Extensive simulations are provided to demonstrate the improved effectiveness and robust capability of the proposed HANC as compared to its counterpart, even in a case that the low-frequency sinusoidal component in the FFANC reference signal is partially corrected with the primary narrowband noise component that is targeted by the FBANC. © 2023 IEEE.

关键词： Filter banks

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Design and Characterization of Printed Flexible Humidity Sensor

Design and Characterization of Printed Flexible Humidity Sen...

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2024 Symposium on Printed and Wearable Sensors and systems, held at the 245th ECS Meeting

作者： Banothu, Akhil Naik Budhraja, Vinay Sundaravadivel, Prabha Fletcher, Reginald Reddy, Krishna Dept. of Electrical and Computer Engineering The University of Texas at Tyler TylerTX75701 United States Crop Production Systems Research Unit USDA StonevilleMS38776 United States

ISBN: (纸本)9781623326784

The development of humidity sensors is essential for applications in the environmental, agriculture, medical and semiconductor industries. This research focused on using advanced printed board circuit (PCB) printing technology to fabricate a humidity moisture sensor. The fabrication of humidity sensor was done using two different polymers: p-HEMA and polyimide, and the performance was compared. Humidity sensors with p-HEMA showed higher capacitance value and more sensitivity than the humidity sensors with polyimide. The variation in sensitivity was higher between the relative humidity from 60% to 90% than between 45% to 60%. © The Electrochemical Society.

关键词： Sensitivity analysis

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Deep Reorganization: Retaining Residuals in TinyML 24

Deep Reorganization: Retaining Residuals in TinyML

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61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Mendis, Hashan Roshantha Kang, Chih-Kai Lin, Chun-Han Chen, Ming-Syan Hsiu, Pi-Cheng Research Center for Information Technology Innovation Academia Sinica Taiwan Graduate Institute of Electrical Engineering National Taiwan University Taiwan Dept. of Computer Sci. & Information Engineering National Taiwan Normal University Taiwan

ISBN: (纸本)9798400706011

Designing intelligent, tiny devices with limited memory is immensely challenging, exacerbated by the additional memory requirement of residual connections in deep neural networks. In contrast to existing approaches that eliminate residuals to reduce peak memory usage at the cost of significant accuracy degradation, this paper presents DERO, which reorganizes residual connections by leveraging insights into the types and interdependencies of operations across residual connections. Evaluations were conducted across diverse model architectures designed for common computer vision applications. DERO consistently achieves peak memory usage comparable to plain-style models without residuals, while closely matching the accuracy of the original models with residuals. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Deep neural networks

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RSSI-Based Distance Triangulation Using A Low-Cost Transceiver: Towards Robust Localization in Agrorobotics 10

RSSI-Based Distance Triangulation Using A Low-Cost Transceiv...

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10th International Conference on Smart Computing and Communication, ICSCC 2024

作者： Wong, W.K. Lease, Basil Andy Lim, Chye Ing Jo, Hudyjaya Siswoyo Juwono, Filbert H. Curtin University Malaysia Dept. of Electrical and Computer Engineering Miri Malaysia Curtin Malaysia Research Institute Curtin University Malaysia Miri Malaysia Curtin University Malaysia Dept. of Mechanical Engineering Sarawak Miri Malaysia School of Engineering and Science Swinburne University of Technology Sarawak Campus Kuching Malaysia Xi'an Jiatong-Liverpool University Dept. of Electrical and Electronic Eng. Suzhou China

ISBN: (纸本)9798350363104

Radio-based tracking systems are highly desired in various asset tracking and autonomous systems. The goal of this research report is to evaluate and validate the regression models that are implemented. Smartphone and ESP32 embedded system devices are used to capture the Received Signal Strength Indicator (RSSI), or radio signal strength, and subsequently use it for regression to acquire the distance. The objective of the research is to evaluate the suitability of such devices for distance triangulation. Results indicate a high correlation when used in the short range (10-20 m). The dataset is sampled using several intervals and ranges at two separate locations, i.e., green field and pavement, in view of possible multipath propagation. Results indicate that there does not seem to be multipath propagation despite the sampling of RSSI at the pavement. The R2 of about 0.9 is acquired when range of 1-10 meters is considered. This implies that almost 90% of variance can be explained by the RSSI variation. This research validates some of the findings by other researchers. © 2024 IEEE.

关键词： Triangulation

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Enhancing Cybersecurity in Sustainable Energy: Regulatory Compliance, Challenges, and Policy Innovations 1

Enhancing Cybersecurity in Sustainable Energy: Regulatory Co...

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1st International Conference on Sustainable Energy Technologies and Computational Intelligence, SETCOM 2025

作者： Saxena, Shruti Saxena, Shivani Tahilramani, Nikunj Patel, Ujjawal Talreja, Vandana P. Patel, Ashish National Forensics Sciences University Dept. of School of Cyber Security & Digital Forensics Gandhinagar India Institute of Advanced Research Dept. of Computer Sciences & Engineering Gandhinagar India Adani Institute of Digital Technology Management Dept. of Big Data Analytics Gandhinagar India R.C.Technical Institute Electrical engg.dept Ahmedabad India Ibm India

ISBN: (纸本)9798331520540

The global switch to renewable energy is both a necessity for sustainable development and climate change mitigation. However, this transition is coupled with unique cyber security issues because of the greater reliance on networked digital systems. This paper identifies significant flaws in the current cyber security regulations and procedures while highlighting their effectiveness in the renewable energy sector. Recent research with the analysis highlighted the necessity of adaptable regulatory tools and the particular vulnerabilities that exist in renewable energy networks. According to the report, stronger regulations on the policymaking side must be enforced: rigorous regulatory compliance, increased robustness, and the incorporation of newer security practices that address changing threats. We explore how the integration of cutting-edge technology such as artificial intelligence (AI) could strengthen system resilience using current case studies like China's renewable energy projects and Germany's Energiewende. Furthermore, the importance of cybersecurity in the attainment of the Sustainable Development Goals (SDGs) is evaluated based on how it supports environmental conservation, economic development, and renewable energy. This research will aid the stakeholders and policymakers in making a safe and sustainable energy future. © 2025 IEEE.

关键词： Clean energy

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