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69 articles for “signal processing techniques”
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The Rise of Fractional Calculus: Novel Applications in Engineering and Biological Systems
Abstract: Fractional calculus (FC) is an advanced mathematical framework that generalizes the classical concepts of differentiation and integration to non-integer, or fractional, orders. This extension of traditional calculus allows for the modeling of complex dynamic systems that exhibit behavior not easily captured by integer-order differential equations. Over the last few decades, fractional calculus has seen a rapid rise in popularity, particularly in applied mathematics, engineering, and biological sciences, due to its …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 7–11 Read article
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Enhancing Smart Grid Resilience Through AI-Based Fault Classification
Abstract: Traditional power grids can be developed into smart grids, and they are comprised of the latest information and communication technologies (ICTs), which are based on establishing the relationship between the conventional electricity systems along with the usage of smart meters and distributed generation. This dynamic improves energy efficiency and the integration of renewables. Well, the dynamic and reversible power injection from Distributed Energy Resources (DERs) creates substantial operational problems. These …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
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Bias Detection and Accuracy Enhancement in Voice-based Banking Authentication Using Deep Learning
Abstract: Biometric systems have become an integral part of how many people access banking services today, and voice verification systems can be a secure and easy-to-use source of banking authentication that does not require any physical contact with the bank or any other person. From the security perspective, these systems would normally provide an effective means of identifying an individual but frequently exhibit bias with respect to demographics such as the …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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Design and Implementation of 256-bit Vedic Multiplier on Reconfigurable Platform
Abstract: Multiplication is a fundamental arithmetic operation in digital signal processing and embedded systems. Traditional multiplier architectures often suffer from increased latency and resource utilization when scaled to higher bit widths. Vedic Mathematics, an ancient Indian technique, offers a novel and efficient alternative. This paper presents the design and implementation of a 256-bit Vedic multiplier using the Urdhva Tiryakbhyam Sutra on a reconfigurable hardware platform, specifically FPGA. The proposed architecture decomposes …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 3, 2025 · pp. 56–65 Read article
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Performance Comparison of Noise-Tolerant, High- Performance CMOS Domino Logic Configurations
Abstract: In high-performance VLSI chip design, domino logic configuration is often preferred over static logic due to its faster operation and smaller area footprint, especially in deep submicron (DSM) technology. However, DSM noise has become a significant challenge in domino-based circuits, leading to compromises in the reliability and signal integrity of integrated circuits (ICs). The switching threshold of domino logic, defined as the input voltage level at which the gate output …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 35–50 Read article
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Music Reactive led using Arduino
Abstract: In recent years, the integration of technology into interactive systems has garnered significant attention. Among the many applications, music-reactive LED systems have become popular, offering dynamic visualizations that respond to audio inputs. This paper explores the development and implementation of a music-reactive LED system using Arduino, focusing on real-time audio signal processing and LED control based on the frequency spectrum of the sound. By utilizing Fast Fourier Transform (FFT) algorithms …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 27–33 Read article
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Power and Area - Aware Recursive Multiplier Architecture Utilizing Polymer Composites for Neural Network Acceleration
Abstract: Approximate computing is widely applied in error - tolerant systems as an effective technique to enhance circuit performance by deliberately allowing occasional inaccuracies instead of strictly ensuring precise results for every computation. Among the fundamental building blocks of digital systems, multipliers play a crucial role in signal processing, control systems, and machine learning applications; however, they demand significant power, silicon area, and timing resources. Leveraging error - tolerant approximate multipliers …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1320–1337 Read article
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Pharmacokinetic Profiling and Molecular Docking of Carvacrol and Structural Analogs: Targeting Quorum Sensing Proteins to Disrupt Biofilm-Mediated Antimicrobial Resistance in Multidrug-Resistant Bacterial Pathogen
Abstract: Antibiotic resistance, particularly in Pseudomonas aeruginosa, has become a major global health threat, exacerbated by the organism's ability to form biofilms and regulate virulence through quorum sensing (QS). The LuxR and LasR receptors are key regulators in this process, influencing both pathogenicity and antibiotic resistance. This study investigates potential QS inhibitors targeting these receptors as a strategy to mitigate antibiotic resistance. The primary objective was to identify novel ligands that …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 3, Issue 2, 2025 · pp. 43–61 Read article
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A Study on Recent Trends in Chemical Sensors for Detecting Toxic Materials
Abstract: Poisonous materials, such as mutagenic, carcinogenic, and poisonous compounds, are widely produced as a result of industrial development. Such materials continue to be hazardous to human health despite stringent management and control procedures. As a result, practical chemical sensors—such as optical, electrochemical, nanomaterial-based, and biological system-based sensors—are needed for the monitoring of dangerous chemicals. For the detection of harmful compounds, numerous new and existing chemical sensors are being created, along …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 3, 2025 · pp. 26–35 Read article
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Current Drugs Target the EGFR
Abstract: Cancer is a devastating disease, but there have recently been significant advancements in therapy that have identified EGFR and its related proteins as valuable indicators and targets for treatment. The ERBB receptor tyrosine kinase superfamily includes EGFR, which is a transmembrane glycoprotein. When the EGFR receptor interacts to its particular ligand, EGF, it causes tyrosine residues to be phosphorylated and forms receptor dimers with other members of the receptor family. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 1–8 Read article
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Drilling Parameters Optimization in LM6/B4C/Fly ash Hybrid Composites by Taguchi Technique
Abstract: Aluminium matrix composites (AMCs) are challenging to machine due to its abrasive characteristics. Because of the broad adoption of MMCs, it is vital to create sufficient equipment to facilitate efficient manufacturing. The current study utilizes signal-to-noise ratio (S/N) analysis to determine the ideal machining parameters for drilling AMC’s. The goal with this study is to investigate the effect of feed rate (FR), drill type (D), speed (SS), reinforcing material R …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 890–897 Read article
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Fractal-Entropy Guided Adaptive Signal Reconstruction for Non-Stationary Biomedical and Communication Systems
Abstract: This paper presents a novel Fractal-Entropy Guided Adaptive Signal Reconstruction (FEG- ASR) framework designed for accurate processing of non-stationary signals in biomedical and communication systems. The proposed approach integrates fractal dimension analysis with entropy- based feature evaluation to capture the intrinsic complexity and irregularity of time-varying signals. By dynamically adapting reconstruction parameters based on fractal-entropy measures, the method effectively separates noise from meaningful signal components while preserving critical information. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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Revolutionizing Wireless Communication: AI & ; ML in the Era of 6G
Abstract: With rapid technological advancement, sophisticated techniques are significantly enhancing the performance of wireless networks. In parallel, the growth of artificial intelligence (AI) has empowered systems to perform intelligent decision-making, automate processes, analyze data, generate insights, and predict future outcomes. AI systems are now capable of learning and adapting to dynamic environments. Particularly, machine learning and deep learning techniques have achieved remarkable success across a wide range of applications in recent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 29–36 Read article
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Efficient Gabor Filter Design Using Verilog HDL with Multiplier-accumulator (MAC) Implementation
Abstract: This paper introduces a novel and enhanced Gabor filter design aimed at addressing the demands of image processing applications using the Verilog Hardware Description Language (HDL). Specifically, it leverages the Reconstruct Gabor filter technique to elevate the performance and quality of standard image outputs. The primary objective of this research endeavor is to simplify the study, conduct an in-depth analysis, and substantially enhance the design's efficiency, all while ensuring the …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 1, Issue 2, 2023 · pp. 40–46 Read article
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Emotion Recognition from Electroencephalogram Signal and Eye Movement Based on Deep Learning
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article
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A Review Paper on The Mathematical Foundations of Artificial Intelligence
Abstract: Artificial Intelligence (AI) is deeply rooted in various branches of mathematics, which provide the theoretical foundation and practical tools for developing intelligent systems. This paper explores the crucial role of mathematics in AI, focusing on key areas such as Linear Algebra, Probability and Statistics, Optimization Techniques, Calculus, Graph Theory, and Fourier and Wavelet Transforms. Linear Algebra is fundamental for representing and manipulating data, with applications in dimensionality reduction and neural …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 7–14 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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Computational Approaches to Understanding Cellular Signaling Pathways
Abstract: Cellular signaling pathways are fundamental in regulating vital processes, such as cell growth, differentiation, and apoptosis. The intricate and interconnected nature of these signaling networks requires sophisticated methods for their analysis. Computational approaches, including mathematical modeling, network analysis, and machine learning, have revolutionized the way researchers analyze and simulate cellular signaling. This article provides a comprehensive overview of computational strategies employed to model signaling pathways, with a focus on integrating …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 8–13 Read article
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Identifying and Implementing a Machine Learning Model Suitable for Processing Visually Evoked Potential
Abstract: A Brain-Computer Interface (BCI) is a system that translates brain activity patterns into computer commands, bypassing physical movement. Electroencephalography (EEG) is commonly used to acquire signals in BCI research. Visual evoked potentials (VEPs) are brain responses in the visual cortex to visual stimuli. Recent studies show that exposing individuals to flickering at a consistent frequency generates EEG signals synchronized with the stimulation. Efficient extraction of VEP signals begins with preprocessing …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Design of an ArUco Marker-Guided Smart Trolley with Integrated Billing Estimation
Abstract: The growing adoption of automation in retail environments has increased the need for intelligent systems that improve user convenience and reduce manual effort. This paper presents the design and development of a human-following smart shopping trolley with an integrated automatic billing system based on computer vision. The proposed system employs ArUco marker–based human tracking to achieve reliable and real-time following behaviour. A Raspberry Pi serves as the central processing unit, …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 Read article