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35 articles for “noise reduction”
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Design and Development of Screw Detection System : A case study
Abstract: This study explores the design of a vision-based screw detection and orientation system for industrial automation, inspection, and robot disassembly. By integrating machine learning algorithms like region-based convolutional neural networks (R-CNN) with traditional image processing and impedance sensing, the system performs real-time screw presence detection, head type identification, and alignment. Three key technologies—deep learning classification, edge-based geometric analysis, and impedance verification—are integrated into a single modular system. The findings indicate …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 30–36 Read article
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Deep Learning Based Detection and Classification of Brain Tumors Using MRI Images
Abstract: Brain tumor detection using magnetic resonance imaging (MRI) is a critical task in the early detection and treatment of brain tumors. Manual analysis of brain tumor detection using MRI is a tedious task that requires expertise in the field. Therefore, this study proposes a deep learning-based approach for brain tumor detection and classification using Convolutional Neural Networks (CNN). The proposed approach preprocesses the MRI image using normalization, resizing, and noise …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Solar Panel Defect Detection Using Geospatially-Aware Deep Learning framework
Abstract: Large-scale photovoltaic (PV) systems demand reliable inspection techniques to maintain efficiency, as manual methods remain labor-intensive and inconsistent. This study introduces a geospatially informed deep learning framework for defect detection and localization in PV panels from drone and satellite imagery. The framework incorporates an adaptive tiling mechanism that adjusts tile boundaries according to object size, reducing information loss and enhancing detection performance. In addition, coordinate transformation between image pixels and …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 2, 2026 Read article
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Optimized Text Extraction and E-Repository Development of Hindi and Punjabi Documents Using OCR and NLP Techniques
Abstract: Increase in digitalization of content in the form of text content necessitates powerful document and text extraction systems, particularly for Indian languages such as Hindi and Punjabi. The existing Optical Character Recognition (OCR) solutions support major scripts such as English, leaving a research opportunity for effective recognition of Devanagari and Gurmukhi scripts. This study recommends a modified text extraction algorithm based on Tesseract OCR, accompanied by preprocessing steps of conversion …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 3, 2025 · pp. 35–43 Read article
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Design of Optimized Full Adder using Noise-Mitigation Techniques and Power Gating
Abstract: With the advent of nanoscale technology, a new era of power consumption, speed, and reliability challenges for traditional static CMOS logic has begun. To solve these problems, dynamic logic families—particularly domino logic—have emerged as potent substitutes that offer quicker processing speeds and lower power consumption. The design and optimization of a full adder circuit using domino logic is shown in this study. A dynamic domino logic technique is used to …
Published in Journal of Microelectronics and Solid State Devices · Vol. 11, Issue 3, 2024 · pp. 1–6 Read article
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Adaptive Drift Correction in Polymer-Based Wearable Biosensors via Data-Driven Signal Modeling
Abstract: Polymer-based wearable biosensors have emerged as a promising technology for continuous health monitoring due to their mechanical flexibility, biocompatibility, and suitability for long-term physiological interfacing. However, prolonged exposure to biofluids, environmental variability, and mechanical deformation introduces signal drift, which significantly degrades measurement accuracy and limits clinical reliability. This paper presents a data-driven methodology for compensating signal drift in polymer-based wearable biosensors using adaptive signal processing and machine learning techniques. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 131–139 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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From Baseline Survey to Management Plan: A Systematic Framework for Port-Specific Mitigation of Underwater Radiated Noise
Abstract: The growing recognition of underwater radiated noise (URN) as a significant marine pollutant necessitates the development of actionable management frameworks at the port level, where noise sources are concentrated, and impacts can be particularly acute. While international guidelines exist, a standardized methodology for ports to transition from assessment to implementation is lacking, particularly in regions with high biodiversity and developing maritime infrastructure. This paper presents and demonstrates a systematic, four-phase …
Published in Journal of Offshore Structure and Technology · Vol. 13, Issue 1, 2026 · pp. 22–30 Read article
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Machine Learning–Guided Cognitive RF System with Dynamic FFT Resolution and Multiplier Reconfiguration for Adaptive Anti-Jamming Communication
Abstract: This paper presents a hierarchical adaptive RF communication system that integrates signal quality-based pre- processing with machine learning-driven signal classification to achieve robust and resource-efficient operation in dynamic, interference-prone environments. Unlike prior art that addresses adaptive RF, ML classification, or anti-jamming individually, this work uniquely combines real-time SNR/RSSI-based signal strength estimation with dynamic FFT size selection (64-, 256- , or 512-point) and arithmetic-level multiplier reconfiguration (CORDIC, Distributed Arithmetic, and hybrid …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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A Systematic Review of Advanced Composite Materials for High-Performance Spur Gear Applications
Abstract: This is a review which provides specific and detailed information regarding the fiber-reinforced polymer (FRP) composite to replace traditional steel in high-performance spur gears with emphasis on mechanical performance, computational modeling, and experimental validation. Methods: The current literature was thoroughly investigated that includes material properties, material simulation (e.g., finite element analysis, FEA), and experimental gear testing procedures (e.g., DIN 51354, ASTM G99). Certain case studies in the aerospace and automotive …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 209–220 Read article
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Optimizing Manufacturing Processes with Taguchi Method in Production Engineering
Abstract: The Taguchi Method, pioneered by Genichi Taguchi, stands as a powerful optimization tool within the realm of production engineering. This paper delves into the principles, applications, and significance of the Taguchi Method in enhancing manufacturing processes. With a focus on minimizing variation and improving performance, this methodology plays a crucial role in addressing challenges faced by industries in their pursuit of operational excellence. The core components of the Taguchi Method, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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Tailoring the Compressive Behavior of Tetra-Chiral Auxetic Structures through FDM Process Parameters
Abstract: This research evaluates how fused deposition modeling (FDM) fabrication process parameters affect the compressive behavior of tetra-chiral auxetic structures created from Polylactic Acid (PLA). Auxetic materials have a number of useful properties, including reversible deformation and high-energy absorbing capabilities, which are beneficial to creating ultra-lightweight structural, protective, and shock-resistance designs. Among the available auxetic topologies, the tetra-chiral configuration is particularly attractive for engineering use, because its rotation-dominated node–ligament deformation gives …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Optical Image Sensing and Analysis of Iron Ore Pellets: A Machine Learning Approach
Abstract: The present work is aimed to improve quality control in steel production using SEM imaging and machine learning. High-resolution SEM images of iron ore pellets, primarily composed of hematite and magnetite, are analyzed to understand their microstructural features, which significantly impact pellet performance during reduction processes. Traditional microstructure analysis is manual, time- consuming, and prone to inconsistencies. This study proposes an automated approach using K-Means Clustering, Canny Edge Detection, DBSCAN, …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 7–18 Read article
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Low-Power Reconfigurable Digital Filter Design Using FPGA for IoT Edge Devices
Abstract: The rapid evolution of the Internet of Things (IoT) has led to an exponential increase in the deployment of edge devices that continuously process real-time sensor data under strict power, latency, and computational constraints. Digital filtering remains a critical operation in these devices, supporting tasks such as noise removal, data conditioning, and feature extraction for intelligent decision-making. However, conventional filter implementations on microcontrollers or fixed digital signal processors often struggle …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 23–34 Read article
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Comparison Between Reed–Solomon and BCH Code with Various Modulation Schemes Over Coding Gain and Coding Rate
Abstract: The main objective of this research paper is to make a comparison between the performance of Reed-Solomon (RS) and Bose–Chaudhuri–Hocquenghem (BCH) codes across different modulation schemes concerning coding gain and coding rate within an additive white Gaussian noise (AWGN) channel system, while maintaining a constant transmission bandwidth. In this paper bit error rate (BER) versus signal/noise (S/N) performance of a Simulink model is validated with MATLAB results for a RS …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 1, 2024 · pp. 32–50 Read article