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41 articles for “Non-linear analysis”
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LQR-Based Optimal Control of Inverted Pendulum System with State Estimation and Stability Analysis
Abstract: The inverted pendulum on a cart is a canonical benchmark problem in control systems engineering, capturing the essential challenges of stabilizing an inherently unstable, underactuated, and nonlinear plant. Classical Proportional-Integral-Derivative (PID) controllers, while widely employed in industrial practice, exhibit fundamental performance limitations when applied to such systems, primarily due to their inability to account for multivariable coupling, process noise, and the absence of a systematic optimization framework. This paper presents …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 1, 2026 · pp. 31–43 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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Dynamic Response Analysis of Isotropic and Orthotropic Rectangular Plates under Clamped-Free Conditions
Abstract: This study explores Theoretical and numerical tools of determining the free vibration properties of isotropic and fiber-reinforced composite rectangular plates. The effect of anisotropy of materials on the dynamic response of the plates is compared between the Aluminium plates and the glass-epoxy laminates. The model used in the study is a three-dimensional finite element model that is designed using a combination of SolidWorks and ANSYS workflow. Clamped-free boundary conditions are …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 258–274 Read article
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Modelling of The Viscoelastic Composite Curved Panel for The Time Domain Analysis Using TTBDF, β1 / β2−Bathe and Newmark Method
Abstract: Viscoelastic materials are extensively used in structures, especially thin-walled structures, for damping. The accurate modelling of the time domain dynamics of the viscoelastic material is essential for appropriately capturing the damping of the viscoelastic material. Various implicit and explicit time integration schemes are available to evaluate time domain response. However, the rightness of the implementation of the time integration scheme to the viscoelastic material model is very essential. In this …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 204–222 Read article
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Algebraic Foundations of AES (Advanced Encryption Standard): Group Theory and Finite Field Applications in Symmetric Cryptography
Abstract: This paper presents a mathematical study of symmetric cryptographic algorithms, with a particular emphasis on the Advanced Encryption Standard (AES), which is one of the most widely used encryption schemes in modern security applications. The study highlights how abstract mathematical frameworks such as group theory, finite fields, and vector space concepts provide the foundation for the design, implementation, and analysis of AES. By approaching the algorithm from a mathematical perspective, …
Published in Recent Trends in Mathematics · Vol. 2, Issue 1, 2025 · pp. 12–16 Read article
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Machine Learning-Based Channel Estimation in 5G, Beyond-5G, and 6G Networks: Recent Advances and Future Directions
Abstract: Accurate channel estimation is one of the most fundamental challenges in modern wireless communication systems. In fifth- generation (5G) New Radio (NR) and emerging sixth-generation (6G) networks, precise knowledge of the wireless channel is essential for achieving reliable data transmission, high spectral efficiency, and low Bit Error Rate (BER). Conventional estimation techniques such as Least Squares (LS) and Minimum Mean Square Error (MMSE) rely on mathematical channel models and predefined …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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Intuitionistic Fuzzy Hypergraph Laplacians and Dominating Transversals for Resilient Discrete Network Design
Abstract: This manuscript develops a discrete mathematical framework for resilience analysis on networks whose interactions are polyadic, uncertain, and partially conflicting. Classical graphs compress multi-way coordination into pairwise edges, while ordinary fuzzy graphs often ignore the non-membership information that becomes critical in emergency logistics, infrastructure interdependence, and cyberphysical coordination. We therefore formulate an intuitionistic fuzzy hypergraph in which each vertex hyperedge incidence carries membership, non-membership, and hesitation, and we construct a …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 15–21 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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Growth, Structural and Optical characteristics of Citric Acid Doped Copper Sulphate Single Crystals Polymer Composites Photonic Applications
Abstract: The organic material Citric Acid doped Copper Sulphate single crystals (CACS) was synthesized and single crystal was grown by slow evaporation method. The incorporation of citric acid, an organic compound, introduces polymer-like functional behavior into the crystal matrix, forming an organic-inorganic hybrid composite with enhanced optical and structural characteristics. Single crystal XRD confirmed the triclinic system with unit cell parameters: a = 5.96 Å, b = 6.11 Å, c = …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 482–488 Read article
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SpecForesight: A Predictive Analytics Pipeline for Laptop Price Forecasting
Abstract: This paper frames laptop pricing as a supervised predictive analytics problem, transforming product specifications into feature-rich signals to forecast price with calibrated regression models and operational guardrails against drift. A structured pipeline ingests tabular listings, performs data cleaning, and engineers domain-informed features (e.g., central processing unit (CPU) family and clocks, graphics processing unit (GPU) tiering, memory/storage density, display, and touch capabilities), followed by encoding and normalization to optimize model learnability. …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 61–71 Read article
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Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
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Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
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A Review on Predicting Wear and Friction of PTFE Composites - Fillers to Machine Learning Models
Abstract: Polytetrafluoroethylene (PTFE) composites, a self-lubricating material with low friction, became an indispensable material in engineering applications where load carrying capacity and wear are crucial. The pure PTFE has poor mechanical strength and wear resistance which can be enhanced by the addition of fillers in appropriate volume fraction. The wear performance is dependent on various factors such as fillers, operating parameters, environmental conditions as well as manufacturing attributes. This makes the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 114–128 Read article
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An Overview on Quantum dot technology in Temperature sensor design
Abstract: Quantumdot (QD) thermometry harnesses the sizedependent electronic structure of semiconductor nanocrystals to translate minute temperature variations into robust optical signals. In this work we present a systematic design framework for QDbased temperature sensors that integrates (i) bandgap engineering through precise colloidal synthesis, (ii) surfacestate passivation to suppress nonradiative pathways, and (iii) a planar photonicreadout architecture compatible with lowcost, CMOSfriendly fabrication. By exploiting the linear redshift of the photoluminescence (PL) peak …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 1, 2026 · pp. 10–17 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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Artificial Intelligence–Assisted Reduced-Order Modeling and Stability Control in Granular Couette Flow
Abstract: This study develops a reduced-order and stability-aware modeling framework for dense granular Couette flow by integrating continuum mechanics, bifurcation analysis, and data-driven stability estimation. Starting from coupled governing equations for momentum, granular temperature, and microstructural evolution, the system is nondimensionalized and reduced using a Galerkin projection consistent with shear-driven boundary conditions. This yields a low-dimensional nonlinear dynamical system that preserves the essential coupling between velocity, fluctuation energy, and structural relaxation. …
Published in Emerging Trends in Chemical Engineering · Vol. 13, Issue 3, 2026 Read article
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Thermoacoustic Properties of 1-Propanol-n-Hexane and 1-Propanol-Cyclohexane Binary Mixtures: A Comparative Study at 298.15 K
Abstract: This study reports the measurement of ultrasonic velocity (U), viscosity (η), and density (ρ) for the binary liquid mixtures 1-propanol–n-hexane and 1-propanol–cyclohexane at 298.15 K over the full composition range (mole fraction 0.1–0.9). From the experimentally measured data, several important thermodynamic and acoustic parameters, including isentropic compressibility (βₐ), acoustic impedance, intermolecular free length, free volume (Vf), and internal pressure (πᵢ), were systematically derived to assess the magnitude and nature of …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 19–30 Read article
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The Awareness–Behaviour Paradox: Media Literacy and Social Media Risk Behaviour Among Nigerian Undergraduates
Abstract: Background: The proliferation of internet-capable devices and social media platforms has created an intricate web of risks for Nigerian undergraduates, including cyberbullying, addiction, misinformation, and exposure to indecent content. While media literacy has been widely proposed in Western scholarship as a sustainable intervention for responsible online behaviour, its protective mechanisms remain insufficiently understood in non-Western contexts, particularly with respect to the psychological pathways through which literacy operates. Objectives: This study …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 121–126 Read article
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Graph Theoretic Analysis of Cyclodextrin Polymers
Abstract: Topological indicators in chemical graph theory are essential tools in cheminformatics, providing valuable insights into molecular structure and properties to make more accurate predictions about the behavior and efficacy of novel compounds in drug design. The macro molecules are correlated with certain derivatives. The derivatives are growing structures which depends on the cyclic structures. The Cyclodextrin is one of the cyclic structures which depends on the carbon atoms. The polymer …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 997–1006 Read article
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Blockchain Enabled IoT System for Tamper Proof Monitoring of Polymer Composite Manufacturing Quality
Abstract: Ensuring real-time process compliance in resin-based polymer composite manufacturing remains a persistent challenge due to non-linear material behaviors, unpredictable curing dynamics, and fragmented sensor data pipelines. Traditional centralized monitoring architectures struggle to guarantee data integrity, auditability, and adaptive response under high-frequency environmental fluctuations. Most existing frameworks fall short in unifying trust, traceability, and time-critical decision-making particularly during critical cure-phase deviations due to limited integration of blockchain with intelligent sensor systems. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 126–145 Read article