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9 articles for “adaptive acoustics”
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Exploring Adaptive Acoustics for Educational Spaces
Abstract: Acoustics play a major role in educational buildings as these have high density, occupying classrooms, lecture halls, conference rooms, auditoriums, etc., engaged by students for several activities. Due to their multi-functional nature, architectural studios in particular require larger spaces and these often accommodate furnishing such as drafting board/table, screens and podium. The considerable volume of these studios can lead to compromised acoustical comfort, which may result in issues like echoes …
Published in International Journal of Architectural Design and Planning · Vol. 2, Issue 2, 2024 · pp. 18–37 Read article
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The Role of Adaptive Filters in Enhancing Acoustic Echo Cancellation Efficiency in Noisy Environments
Abstract: The novel approach that this work discusses is a DCD-based iterative learning filter approach improved with deep learning methodologies, designed to improve the efficiency of acoustic echo cancellation. The proposed system can really manage both linear and nonlinear echo scenarios, dynamically adapting to fluctuating acoustic environments. The above comparative evaluations with standard filter, the standard RLS filter, indicate that the mean square error, and the standard deviation of the correlation …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 2, 2024 · pp. 9–24 Read article
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Traffic Management System using Divider Shifting Mechanism
Abstract: This paper addresses traffic congestion through innovative solutions, including movable dividers that adjust road configurations and lanes dynamically. Real-time monitoring, using sensors and cameras, coupled with advanced algorithms, optimizes traffic flow by reallocating lanes according to changing conditions such as rush-hour congestion or accidents. Additionally, the system integrates variable speed limits and dedicated lanes for pedestrians and cyclists to enhance safety and accommodate diverse transportation modes. Centralized integration with a …
Published in Journal of Production Research & Management · Vol. 14, Issue 1, 2024 · pp. 21–28 Read article
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Polymer-Based Acoustic Composite Materials for Urban Noise Mitigation: Design, Performance and Legal Integration
Abstract: This study explores the development and use of polymer-based acoustic composite materials for effective urban noise mitigation, wherein the performance of the materials is linked to legal compliance frameworks. Rapid urbanization has intensified noise pollution from transportation, industrial activity, and construction, posing a serious threat to public health and environmental quality. Although regulatory standards exist, their implementation is often limited due to inadequate technical interventions. This research focuses on advanced …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 403–412 Read article
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A Review of Torque Ripple Reduction Techniques in Switched Reluctance Motors
Abstract: Switched Reluctance Motors (SRMs) have emerged as a promising alternative to conventional motor technologies due to their rugged structure, low manufacturing cost, high-temperature capability, and suitability for harsh environments. Despite these advantages, the widespread adoption of SRMs in applications such as electric vehicles, household appliances, industrial drives, and aerospace systems is significantly restricted by the issue of torque ripple. Torque ripple manifests as periodic fluctuations in the developed electromagnetic torque, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 45–50 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 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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Deep Learning for Real-Time Monitoring and Defect Detection in Additive Manufactured Polymer Composites
Abstract: Additives Fiber-reinforced polymer composite ADDs have high utility in making lightweight structural components, but due to process-related defects (interlayer delamination and reinforcement stacking) the integrity of consolidation during extrusion-based deposition is frequently compromised. This paper has presented a physics-informed deep learning framework that is applicable to real-time measurements of reinforced thermoplastic composite fabrication. Multimodal sensing was provided with thermal gradient, optical morphology, and acoustics emission signals being used to assess …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 974–999 Read article
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Data-Driven Life Prediction of Fiber-Reinforced Polymer Composites Using IoT Sensing and Machine Learning Algorithms
Abstract: The accurate prediction of fatigue life in fiber-reinforced polymer (FRP) composites remains a major challenge due to their nonlinear, multi-mechanism degradation behavior under variable loading conditions. This study presents a data-driven framework, H-LiProNet, which combines real-time IoT sensing with hybrid machine learning to estimate remaining useful life (RUL) in FRP composites. The proposed system integrates embedded Fiber Bragg Grating (FBG) and acoustic emission (AE) sensors to capture strain and damage …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 116–130 Read article