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Advanced Federated Spectrum Busting: Federated Learning-Based Transmitter Identification system for Conventional Warfare and Counter Terrorism 5th

Advanced Federated Spectrum Busting: Federated Learning-Base...

引用

5th international conference on Electrical and Electronics Engineering, ICEEE 2024

作者： Satapathy, Jyoti Ranjan Ayeelyan, John Bodade, R.M. Faculty of Communication Engineering Military College of Telecommunicatiion Engineering Madhyapradesh Indore India

ISBN: (纸本)9789819790364

The escalating demands of modern wireless communication has increased the number of transmitters, and this has highlighted the necessity of security, availability, and data privacy for both military and civilian applications. Radio fingerprinting using Software Define Radio (SDR) (Akeela and Dezfouli in Comput Commun 128:106–125 in [1]) can be used to identify the transmitters which can give adequate decisive dividends in both conventional and anti-terrorism warfare. This paper presents a novel hybrid method for radio fingerprinting through RF classification. Further, it recommends the Federated learning (FL)-based self-learning model of Radio Fingerprinting for Defense forces which showcase 0.92 accuracy of our client model and 0.94 accuracy of universal model. The implementation encompasses critical aspects including spectrum sensing, signal classification, automatic parameter adaptation, countering spoofing attacks and fingerprint-based authentication, data privacy, and edge computing. Further, the solution is going to ensure all requisite parameters of security, availability, low latency and reduced power, processing, storage and bandwidth usage which is critical in a battle field of conventional warfare and anti-terrorism operations. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Terrorism

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Design and Simulation of Low power Leakage-Controlled SRAM Cell

Design and Simulation of Low Power Leakage-Controlled SRAM C...

引用

international conference on signal processing and communication (ICSC)

作者： Avinash Singh Rajeev Kumar Chauhan Saurabh Kumar Prince Kumar Singh Dept. of Electronics and Communication Engineering Madan Mohan Malaviya University of Technology Gorakhpur Uttar Pradesh

ISBN: (数字)9798331511890

ISBN: (纸本)9798331511906

Since the dawn of the 21st century, the rise of IoT-powered portable devices has sparked a revolution in low-power SRAM development. As the complexity of such devices has exponentially increased to support a higher number of operations, advanced power management techniques are now essential to minimize power consumption. Consequently, low-power circuit design continues to be a prominent area of research. This paper introduces an innovative low-power SRAM cell design that surpasses traditional options. Compared to conventional 6T SRAM and DTMOS-based SRAM cells, simulations demonstrate that the proposed design significantly reduces power consumption without compromising propagation delay, marking a promising advancement in SRAM technology. The simulations were conducted using the Siemens Tanner EDA Tool version 2022.2. The supply voltage and operating frequency were set to 2V and 100MHz, respectively.

关键词： power demand power system management Voltage signal processing SRAM cells Complexity theory Circuit synthesis Integrated circuit modeling Propagation delay

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Networked ISAC Beamforming Design with Capacity-Limited Fronthaul Links

Networked ISAC Beamforming Design with Capacity-Limited Fron...

引用

international conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Kexin Zhang Yanqing Xu Tsung-Hui Chang School of Electronic and Information Engineering Beijing Jiaotong University Beijing China School of Science & Engineering The Chinese University of Hong Kong Shenzhen China Shenzhen Research Institute of Big Data Shenzhen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

This study investigates a networked integrated sensing and communication (ISAC) system, where a central processor coordinates multiple ISAC transmitters and a sensing receiver through capacity-limited fronthaul links. The system aims to serve multiple mobile users and simultaneously sense a point target. The primary objective is to minimize the total transmit power while meeting the minimum signal-to-interference-plus-noise ratio (SINR) requirements for both communication and sensing, as well as adhering to the fronthaul capacity constraints. This leads to a complicated joint fronthaul compression and beamforming design (J-FCBD) problem. Although the J-FCBD problem is challenging to solve, we demonstrate that the optimal fronthaul compression variables can be determined in closed form alongside the beamformers. This novel finding has not been previously reported in the literature. Leveraging this insight, we prove that the remaining problem can be globally solved using the semidefinite relaxation (SDR) technique. Simulation results verify the effectiveness of the proposed design.

关键词： Array signal processing Transmitters Simulation system performance signal processing algorithms Interference Integrated sensing and communication Solids Speech processing signal to noise ratio

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Bidirectional Spiking Neuron Based Dual-Mode signal Acquisition Front-End system

Bidirectional Spiking Neuron Based Dual-Mode Signal Acquisit...

引用

international conference on VLSI Design

作者： Tamal Chowdhury Pradip Mandal Department of EECE IIT Kharagpur Kharagpur India

ISBN: (数字)9798331522445

ISBN: (纸本)9798331522452

In this work, we propose a Bidirectional Spiking Neuron (BSN)-based signal acquisition front-end system, generating signals suitable for processing through bidirectional Neural Networks. The proposed system has two operating modes, namely surveillance and precision. In surveillance mode, it consumes very low power; however, it provides compromised precision. On the other hand, in precision mode, its linearity is enhanced but with a cost of power dissipation. The proposed circuit has been designed and simulated in TSMC 65 nm technology node with a 1.2 V power supply. The input signal handling capacity of the proposed design is up to $2\ \mu \mathbf{A}_{p-p}$ . In the surveillance mode of operation, for a low-frequency input signal of 250 nA amplitude, the proposed front-end system achieves up to 38 dB SNDR with less than 250 nW power consumption. In contrast, for the same input signal, the design attains 49 dB SNDR in precision mode. However, the peak SNDR achieved in precision mode is 53.6 dB. With such flexibility, the proposed BSN can be utilized as a front-end signal acquisition system for Spiking Neural Networks. The design consumes a silicon area of only 0.0034 mm 2 .

关键词： power demand Surveillance Neurons Linearity Spiking neural networks Very large scale integration Silicon Sensor systems Sensors Tuning

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An Optimized Multiply Accumulate Unit for embedded Applications 5

An Optimized Multiply Accumulate Unit for Embedded Applicati...

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5th IEEE international conference on Advances in Electrical, Computing, communication and Sustainable Technologies, ICAECT 2025

作者： Kartheek, S.V. Sudeep, T.V. Harish, P. Vinodhini, M. Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350356236

In recent years, several embedded applications have made use of Multiply-ACcumulate (MAC) units, from signal processing to artificial intelligence. The basic blocks of MAC units are Multiplier, Adder, and Accumulator. The design and performance of MAC units are crucial because they directly affect the speed, power consumption, and total computing capability of the systems in which they are utilized. In the proposed work, a low-power MAC unit architecture is designed. Two-Stage Carry Select Adder (TSCSA) uses two types of cells which are 2:1 Multiplexer and NAND gates are used for adder design and Optimized Counter-Based Multiplier (OCBM) is used for multiplier design in MAC units. The experiment's findings indicate that, in comparison to the current MAC unit architecture, the suggested solution uses a 29.3% reduction in power, a 6.48% reduction in area, and a 3.34% reduction in delay. © 2025 IEEE.

关键词： Physical addresses

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3rd international conference on Machine Vision and Augmented Intelligence, MAI 2023

3rd International Conference on Machine Vision and Augmented...

引用

3rd international conference on Machine Vision and Augmented Intelligence, MAI 2023

ISBN: (纸本)9789819743582

The proceedings contain 76 papers. The special focus in this conference is on Machine Vision and Augmented Intelligence. The topics include: Survey on Robustness of Deep Learning Techniques on Adversarial Attacks in WBAN;synergizing Collaborative and Content-Based Filtering for Enhanced Movie Recommendations;exploring Transformer-Based Approaches for Hyperspectral Image Classification: A Comparative Analysis;deep Learning for Cognitive Task and Seizure Classification with Hilbert–Huang Transform and Variational Mode Decomposition;tracking of Ship and Plane in Satellite Videos Using a Convolutional Regression Network with Deep Features;Tumor Detection and Analysis from Brain MRI Images Using Deep Learning;software Maintenance Prediction Using Stack Ensemble Deep Learning Algorithms;resource Allocation in 6G Network for High-Speed Train Using D2D Outband communication;controlling the Band-to-Band Tunneling Effect in Charge Plasma Based Dopingless Transistor;Comparison of Different CIC Filter Architectures on the Basis of a Novel Parameter Called Noise Factor for Sigma-Delta Based ADCs;the Scientific Analysis on Effective Yoga Posture Recognition Techniques;impact of Gamma Rays on Emerging Devices for Photonic Applications;shaft Rotation Monitoring Using Radar signal processing and Wavelet Transform;gysel power Divider Miniaturization Using an Inter-Digital Capacitor-Based Slow-Wave Structure;noise Estimation and Removal in Fundus Images Using Pyramid Real Image Denoising Network;evaluation of Hybrid Encryption Method to Secure Healthcare Data;multimodal Face Recognition system Using Hybrid Deep Learning Feature;Classification of Copy and Move Image by Using HELM-FSK Method: An Efficient Approach;analysis of Energy Efficient Smart Home Based on IoT system;role of Explainable Artificial Intelligence Approaches in Cybersecurity.

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Real-Time Wild Animal Detection using YOLOv10 Algorithm

Real-Time Wild Animal Detection using YOLOv10 Algorithm

引用

international conference on Wireless communications, signal processing and Networking (WiSPNET)

作者： Nishanth I Rakeshkumar R Thenmozhi V Department of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Chennai India

ISBN: (数字)9798331524227

ISBN: (纸本)9798331524234

This project utilizes the YOLOv10 algorithm on the NVIDIA Jetson Nano board to create a real-time wild animal detection system. By continuously analyzing video feeds from wildlife monitoring setups, the system accurately and efficiently detects animals across diverse environmental conditions. Leveraging the Jetson Nano’s edge computing capabilities alongside YOLOv10’s advanced object detection, the research presents a cost-effective, low-power solution for automated wildlife monitoring. With its ability to continuously track and identify animals in remote areas, this approach enhances conservation efforts and provides valuable data for biodiversity studies and the protection of endangered species.

关键词： YOLO Wireless communication Animals Biological system modeling Surveillance Wildlife signal processing algorithms Streaming media Real-time systems Environmental management

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Energy Harvesting Optimization in FSO communication with SLIPT Using Advanced Splitting Methods

Energy Harvesting Optimization in FSO Communication with SLI...

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international conference on Wireless communications, signal processing and Networking (WiSPNET)

作者： Angayarkanni V Sheeba A Dharshini V M Suvetha P Kavitha Kamatchi Suveetha Dhanaselvam P Karthikeyan B Prabu Krishnan Department of Computing Technologies SRM Institute of Science and Technology Tamil Nadu India Department of Electronics and Communication Engineering Velammal College of Engineering and Technology Madurai India Department of Electronics and Communication Engineering National Institute of Technology Karnataka India

ISBN: (数字)9798331524227

ISBN: (纸本)9798331524234

This paper presents an analysis of Simultaneous Lightwave Information and power Transfer (SLIPT) in FreeSpace Optical (FSO) communication systems, incorporating key techniques such as AC-DC Separation (ADS), power Splitting (PS), Time Switching (TS), and a hybrid Time Switching-power Splitting (TS-PS) scheme. Closed-form expressions for the average harvested energy are derived, considering FSO turbulence channels modeled using the Málaga distribution. Furthermore, the analysis evaluates the impact of various turbulence conditions, including clear air, heavy rain, drizzle, and light fog, as well as the influence of receiver aperture size and other system and channel parameters. The primary focus of the result is to assess the energy harvesting performance under these diverse operating conditions.

关键词： Wireless communication Closed-form solutions Rain Optical switches Apertures Optical receivers Energy harvesting Optical sensors Optical signal processing Optimization

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Enhancing Induction Motor Reliability Through Advanced Feature Selection and Diagnostic Models in Low-Load Conditions

Enhancing Induction Motor Reliability Through Advanced Featu...

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international conference on Artificial Intelligence in Information and communication (ICAIIC)

作者： Chibuzo Nwabufo Okwuosa Jang-Wook Hur Department of Mechanical Engineering (Department of Aeronautics Mechanical and Electronic Convergence Engineering) Kumoh National Institute of Technology Gyeonsangbuk-do Republic of Korea

ISBN: (数字)9798331507022

ISBN: (纸本)9798331507039

In induction motors, stator windings are critical for optimal magnetic field distribution, influencing rotor bar induction and motor performance. Motor component failure is undesirable and often necessitates system overhauls. This paper presents a comparative analysis of feature selection techniques filter-based, wrapper-based, and embedded methodsfor diagnosing stator winding faults in squirrel cage induction motors and selecting a reliable cost-efficient feature selection technique with high efficiency. These techniques are applied using varying motor current data signals under low-load conditions. By leveraging advanced signal processing tools, the study demonstrated that the embedded techniques presented a superior computational efficiency and diagnostic model than the other techniques using the XGboost classifier algorithm. Preliminary results highlight the potential of these techniques to improve fault detection while addressing challenges such as noise and signal complexity. Future research will explore the integration of Explainable AI (XAI) to enhance transparency and trust in diagnostic models.

关键词： Induction motors Explainable AI Magnetic separation Noise Stator windings signal processing algorithms Rotors Transforms Feature extraction Information filters

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Design of Pelletizer Automation based embedded system for Soap Oil Factory

Design of Pelletizer Automation based Embedded System for So...

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Device Intelligence, Computing and communication Technologies, (DICCT), international conference on

作者： Sathish Kumar Shanmugam Koushik Nagarajan Ragavi Ravichandran Manjuragavi Ramasamy Sameera Sara Shajahan Department of Electrical and Electronics Engineering M. Kumarasamy College Of Engineering Karur India

ISBN: (数字)9798331543358

ISBN: (纸本)9798331543365

A SIBY Solvents Extraction Private Limited (Soap Oil factory) located near Chinna Salem has a major problem in Pelletizer control. This problem mainly depends on load control like handling coal and other raw materials by the *** embedded system based design consists of a controller which is used to measure the current and voltage rating for the Pelletizer. Based on the above parameters the power of the motors can be calculated simultaneously. The solution of the problem is solved by setting the lower limit and upper limit of current value for the motor. If the motor current is greater than set value the contactor, will cut the power supply to the motor. If the motor current less than set value it generates the on signal to the motor. In addition with that the on time and off time of the motor will be stored to the controller for the future reference. IoT based Monitoring is implemented here. The workers from the industry can't control the pelletizer within in a time due to its control panel distance and lack of language communication.

关键词： Temperature sensors Voltage measurement power supplies Oils Motors Real-time systems Production facilities Safety Monitoring Standards

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