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69 articles for “Noise generation”
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Diffusion-Based Enhancement of Low-SNR Time- Frequency Signals
Abstract: Traditional enhancing techniques are useless in low signal-to-noise ratio (LSNR) situations because noise drastically interferes with communication signals. Based on an enhanced DiffBIR model, this paper suggests a dual-stage signal improvement approach that combines diffusion with deep learning. By combining the Inception module for multi-scale feature extraction with the Pixel Fusion Attention (PFA) module for significant region highlighting, the model improves signal recovery in the time- frequency domain. Experiments show …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 15–27 Read article
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Autonomous Calibration of Medical Devices Using Synthetic Biosignals and Adaptive Learning
Abstract: The accuracy and reliability of modern biomedical diagnostic devices are critically dependent on effective calibration mechanisms capable of handling dynamic physiological and environmental variations. Conventional calibration approaches, which rely on static reference signals and manual adjustments, are inadequate in addressing challenges such as sensor drift, noise interference, motion artifacts, and long-term performance degradation. To overcome these limitations, this research proposes an innovative AI-driven adaptive biosignal simulation and calibration architecture for …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article
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Cutting- Edge Gravitational-Wave Detectors: Technology & Innovations
Abstract: Gravitational wave detectors using laser interferometry are sophisticated instruments designed to measure the ripples in spacetime caused by cosmic events such as the merging of black holes or neutron stars. This schematic outlines the fundamental components and working principle of a typical laser interferometric gravitational wave detector, such as those used in the LIGO and Virgo observatories. The core of the detector is an interferometer, typically a Michelson interferometer, with …
Published in International Journal of Universe · Vol. 1, Issue 1, 2025 Read article
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Harnessing Artificial Intelligence for Precision Physics: A Machine Learning Framework for Data Reconstruction in Support of India's Deep-Tech Missions
Abstract: India's emergence as a global leader in deep-tech innovation is driven by ambitious scientific megaprojects, including the Laser Interferometer Gravitational-Wave Observatory (LIGO)-India, the X-ray Polarimeter Satellite (XPoSat), the Aditya-L1 solar observatory, and the National Quantum Mission (NQM). However, the unprecedented scale and complexity of the observational data generated by these missions present severe computational bottlenecks. Traditional analytical frameworks struggle with non-stationary noise transients, diffusion blurring, and the exponential scaling limits …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 2, 2026 · pp. 48–55 Read article
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High Performance Multi-Valued Logic (MVL)Gate Design Using FinFET
Abstract: CMOS scaling faces challenges such as leakage, power dissipation, and short channel effects. Multi-Valued Logic (MVL) offers higher information density and reduced interconnections. This work presents a FinFET-based MVL gate design that improves electrostatic control, switching speed, and reliability. Simulation results confirm reduced leakage power and enhanced performance compared to conventional logic. The proposed architecture demonstrates scalability for advanced technology nodes. It also shows potential for low-power applications in portable …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 34–45 Read article
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DDoS Detection Using Cascade Correlation for Improving Network Resources in Cloud Environment
Abstract: Intrusion detection is critical for protecting network security from emerging cyber threats. This study describes a unique intrusion detection system (IDS) based on the Random Forest algorithm. Random Forests are used as an effective classifier to identify patterns linked with malevolent behaviour. This technique uses Random Forests to improve the accuracy and efficiency of intrusion detection systems. The suggested methodology's value is shown by its performance on the benchmark KDD …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 17–22 Read article
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State of the Art: A Pandemic Big HealthCare Analytics Solution: Image Data Classification Using Quantum MAML
Abstract: The modern age is facing many pandemic healthcare problems, e.g., covid 19, infections, inflammations, and many more, leading to critical, deadly situations. Survival rate can be increased with proper diagnosis of such data. We have proposed one of the implementations based on a medical image dataset for classification using deep reinforcement learning (RL) with quantum computing. Deep RL is the combination of DL (deep learning), generative adversarial network (GAN), and …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 1–9 Read article
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Graphene–Perovskite Hybrid Opto-Electronic Modulators for Ultra-Low Power Optical Communication
Abstract: This paper proposes a novel self-adaptive neuromorphic opto-electronic transceiver architecture designed to enhance the intelligence, adaptability, and efficiency of next-generation optical communication networks. The proposed system integrates neuromorphic computing principles with photonic signal processing to enable real-time learning, dynamic resource allocation, and autonomous compensation of channel impairments such as dispersion, nonlinearities, and noise. Unlike conventional transceivers, the developed model employs spiking neural networks embedded within opto-electronic circuits to mimic biological …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 1, 2026 · pp. 41–52 Read article
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AI Voice Detection Tool
Abstract: In today’s digital era, distinguishing between AI-generated and human voices is more important than ever. This project introduces an AI-based voice detection system designed to accurately identify synthetic voices, ensuring security and authenticity across various applications like cybersecurity, media verification, and fraud prevention.Our system works by analyzing incoming audio samples and comparing them against a diverse database of both AI-generated and real human voices. Using advanced machine learning and signal …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 1–8 Read article
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Olfactory Intelligence in Bio-Hybrid UAVs: Integrating Living Lepidoptera Sensors for High-Precision Environmental Monitoring
Abstract: Autonomous aerial systems still face major challenges when attempting to locate airborne volatile organic compounds because many conventional gas sensors react slowly and cannot reliably follow turbulent chemical plumes. To address this limitation, a bio-hybrid sensing approach was explored using the antenna of the silkworm moth, Bombyx mori, as a natural chemical detector. The antenna was connected to an Electroantennogram (EAG) system that converts biological nerve signals into digital signals …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 4, Issue 2, 2026 Read article
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Face And Spoofing Detection Via Genetic Algorithm-Based Feature Selection with MTCNN
Abstract: Face detection and liveness detection in various environments such as different lighting effects, occlusion, complex backgrounds, and different poses and angles play an important role in facial recognition or detection purposes. In this research paper, propose an improved algorithm for face detection and liveness, spoofing detection via genetic algorithm for feature selection, and mtcc detecting the edge of the facial image by Canny filter and spotting the face from the …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 1, 2025 · pp. 17–26 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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Innovative Applications of Smart Materials in Aviation: A Comprehensive Review
Abstract: Smart materials are transforming the aviation industry by offering innovative solutions that enhance performance, safety, and sustainability. The use of smart materials can enhance the efficiency, safety, and longevity of aerospace structures by sensing, responding, and adjusting to environmental changes in real time. The objective of this review is to examine how smart materials can be used in aviation, especially in the field of sensor networks, control systems, and structural …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 114–132 Read article
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Evaluation of Optimal Parameters for Wire EDM Machine on En45A Alloy Steel using Taguchi and Grey Relational Analysis (GRA) Method
Abstract: The core goal of this research paper is to evaluate process parameters of wire electrical discharging machining and to find out the best parameter among the multiple responses given by machine. Wire cut machine is very accurate and precise machine which is actually manufactured to cut those material which have high strength, toughness, and hardness. This machine works on melting property; here spark is generated between the work piece and …
Published in Journal of Materials & Metallurgical Engineering · Vol. 6, Issue 1, 2016 · pp. 11–21 Read article
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A Comprehensive Review of CMOS Analog Circuit Design Techniques for Low-Power VLSI Systems
Abstract: CMOS analog circuit design plays a significant role in the development of modern low-power Very Large-Scale Integration (VLSI) systems used in wireless communication, biomedical devices, portable electronics, embedded systems, and Internet of Things (IoT) applications. Research on low-power CMOS analogue design methodologies has intensified because to the growing need for high-performance, small, and energy-efficient electronic products. However, reducing power consumption while maintaining signal accuracy, noise performance, stability, bandwidth, and overall …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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A Comprehensive Investigation of Bagging-Based Ensemble Methods for Improving Machine Learning Model Robustness
Abstract: Machine learning models such as Decision Trees, Logistic Regression, and K-Nearest Neighbors are widely used for classification tasks due to their simplicity and interpretability. However, these models often suffer from high variance, overfitting, and poor generalization when applied to real-world datasets, particularly those that are small, noisy, or imbalanced, as commonly encountered in healthcare, finance, and cybersecurity applications. To address these limitations, this research proposes a Bagging (Bootstrap Aggregating)-based ensemble …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 24–34 Read article
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How small circuits power big technology in the world of VSIL
Abstract: Very Small Integration Level (VSIL) circuit technology represents an emerging class of ultra- compact, low-power electronic design methodologies that enable the creation of highly efficient and scalable systems. This article explores the fundamental principles behind VSIL circuits, including device miniaturization, optimized layout strategies, adaptive power management, and noise-resilient architectures. We also look into the methodical engineering of VSIL circuits to satisfy the ever-tougher performance, robustness, and long- term energy-efficiency demands …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 44–53 Read article
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Binary GA for Sidelobe Reduction and Null Steering in 5G Array
Abstract: This paper presents a comprehensive performance evaluation of a Binary Genetic Algorithm (BGA) for optimizing radiation characteristics of an active phased array antenna used in fifth-generation (5G) wireless communication systems. The primary objective is to achieve effective null steering while maintaining the desired main beam direction and simultaneously reducing the side lobe level (SLL). These improvements are essential for minimizing co-channel interference, enhancing spatial selectivity, and improving the Signal-to-Interference-plus-Noise Ratio …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 2, 2026 Read article
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Harmonic Compensation in Grid Interconnected DG Units by Closed Loop Control
Abstract: This paper deals with improvement of power quality problem namely harmonic problem using distributed generation as their source of electricity. The harmonics occur in such a system because of the nature of loads connected. There are many power quality problems; out of which harmonics normally caused by nonlinear loads like variable frequency drives, fluorescent lightning, office computers etc. have adverse effects on the power quality. Also, harmonic detection and prediction …
Published in Journal of Power Electronics and Power Systems · Vol. 7, Issue 1, 2017 · pp. 9–17 Read article
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Implementation of Kalman Filter Using TDC and PLL for Object Detection and Tracking in Signal Processing
Abstract: The measurement uncertainty of GPS receivers is dependent on a wide range of external factors, including receiver clock precision, thermal noise, atmospheric influences, and minute variations in satellite positions. Estimating hidden states precisely and accurately in the face of uncertainty is one of the main problems facing tracking and control systems. Among the most significant and widely used estimate methods is the Kalman Filter. It uses imprecise and erratic measurements …
Published in Current Trends in Signal Processing · Vol. 13, Issue 2, 2023 · pp. 38–47 Read article