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12 articles for “Wide Linear Range”
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Enhanced Sensitivity Iontronic Pressure Sensor Gauge Using Laser-Created Micro-Pyramid Structures for Wide Linear Range
Abstract: The achievement of high sensitivity, ultrahigh pressure resolution, and great linearity across a wide pressure range under huge pressure preloads remains a challenge despite the substantial development of flexible capacitive pressure sensors. Here we offer an ultrathin ionic layer-integrated microstructure creation process that is configurable. At 1700 kPa, the sensor's linear range sensitivity is 33.7 kPa-1; at 2000 kPa, the pressure resolution is 0.00725%, and the detection limit is 0.36 …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 107–118 Read article
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Comparison of 11-Atom Armchair Graphene Nanoribbons and Zig-Zag Carbon Nanotubes in Polymer Composites Under Various Bias Voltages: A Study of Electronic and Transmission Properties
Abstract: In this research, 11-atom zig-zag carbon nanotubes (ZCNTs) and 11-atom armchair graphene nanoribbons (AGNRs) were studied under applied bias voltages at 50, 150, and 300 millivolt levels. The focus was on understanding their behaviour concerning transmission qualities, current-voltage (I-V) characteristics, and energy-momentum (E-K) diagrams. The Non-Equilibrium Green's Function (NEGF) approach was employed to analyse various electronic properties for ZCNTs and AGNRs, including transmission, E-K relationships, and I-V characteristics. The results …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 126–134 Read article
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Fabrication of Polydimethylsiloxane Composites with Nickel Nanoparticles: Unification and Current–Voltage Relationship
Abstract: Polydimethylsiloxane (PDMS)–nickel nanoparticle (NiNPs) nanocomposite films were fabricated and systematically investigated to understand their electrical transport behavior through current–voltage (I–V) characterization. Nanocomposite films with varying Ni nanoparticle filler concentrations (14.88 wt%, 15.77 wt%, and 16.65 wt%) were prepared using a solution-mixing and spin-coating technique, followed by controlled thermal curing. The electrical properties of both pristine PDMS and PDMS– NiNPs nanocomposites were examined over a wide voltage range (up to 800 …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 16, Issue 1, 2026 · pp. 22–29 Read article
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Proposed System: Quantum Computing Processor Based on Linear Number Relation
Abstract: This paper details the design and implementation of a specialized quantum processor tailored for efficiently evaluating custom mathematical formulas. Optimized to perform a specific set of arithmetic and logical operations, this processor delivers a stable and high-performance computing platform. Unlike general-purpose quantum processors, which are designed for versatility across a wide range of algorithms, this dedicated processor aims to enhance performance and accuracy for a targeted set of tasks. The …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 3, 2024 · pp. 24–32 Read article
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Perturb and Observe Maximum Power Point Tracking Technique with PID Controller for a Wind Power System
Abstract: The wind power generation system has a significant growth worldwide over the past four decades. The wind power generation system has strong coupling and linear characteristics which makes it a complicated electromechanical system. The power control strategy has a higher impact on the overall performance as the wind power generation is operated at variable and random wind speed conditions. PID control is the most used control algorithm in industrial applications. …
Published in International Journal of Advanced Control and System Engineering · Vol. 1, Issue 1, 2023 · pp. 15–25 Read article
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Visual Recognition with Convolutional Neural Networks for Object Detection
Abstract: Various research and development have taken place over the years on computer vision which is a branch of AI. AI disciplines like a vision system is applied in various fields like self-driving cars, face detection by social media apps and law enforcement software’s google lens and so on. The proposed system deals with design and implementation of an efficient way of training a GPU using python libraries to process and …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 07–13 Read article
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Topology and Geometry in Data Science: Persistent Homology and Beyond
Abstract: In recent years, the interplay between topology, geometry, and data science has gained substantial momentum, offering powerful frameworks to analyze and interpret complex datasets. Traditional statistical and machine learning methods often rely on linear or metric- based assumptions, which may fail to capture the intrinsic structure of high-dimensional or nonlinear data. In contrast, topological and geometric methods provide shape-oriented, scale- invariant tools that focus on the continuity, connectivity, and global …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 21–27 Read article
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Multifunctional and Photocatalytic Properties of DyFeO₃/Dy₃Fe₅O₁₂ Biphasic Nanoparticles
Abstract: Rare-earth orthoferrites constitute a class of compounds that exhibit remarkable magnetic, optical, and electronic properties across a wide temperature range. In the present study, a dysprosium-based orthoferrite containing dual phases of DyFeO₃ perovskite and Dy₃Fe₅O₁₂ garnet was successfully synthesized via the co-precipitation technique. X-ray diffraction (XRD) analysis was employed to investigate the structural configuration of the synthesized material. The diffraction pattern confirmed the formation of a biphasic composite comprising orthorhombic …
Published in International Journal of Crystalline Materials · Vol. 2, Issue 2, 2025 · pp. 41–54 Read article
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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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Optimizing Chromatographic Techniques for Comprehensive Paraben Analysis to Enhance Safety in Consumer Products
Abstract: Parabens (PBs), such as methylparaben (MePB), ethylparaben (EtPB), propylparaben (PrPB), and butylparaben (BuPB), are widely used as preservatives in pharmaceuticals, food, and personal care products due to their antibacterial properties. However, there are growing worries about their potential to disrupt hormonal functions, which has led to stricter regulations. This study focuses on creating a robust high-performance liquid chromatography (HPLC) method for quickly measuring all four parabens in consumer goods. We …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 228–243 Read article
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Genomic Selection for Grain Yield in Wheat Using Machine Learning on DArT Molecular Markers: A Comparative Evaluation Across Multi-Environment Trials
Abstract: Genomic selection (GS) predicts complex quantitative traits directly from genome-wide molecular markers, bypassing the need for extensive phenotypic trials and accelerating plant breeding cycles. We conducted a comparative evaluation of seven regression approaches — ridge regression (the machine-learning equivalent of RR-BLUP), Lasso, Elastic Net, Partial Least Squares, linear Support Vector Regression, Random Forest, and Gradient Boosting — for predicting grain yield from 1,279 Diversity Array Technology (DArT) molecular markers genotyped …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article