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90 articles for “Stability-indicating method”
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The Influence of Soil Types on the Performance of the Building Frames: A Dynamic Analysis
Abstract: The dynamic response of the building structure is to a large extent dependent on the nature of the supporting soil. Soil stiffness and damping metrics fluctuation can cause significant tension in the behaviour of building skeleton when exposed to dynamic loads such as earthquake or wind. This research aims to evaluate how different soil conditions namely hard, medium, and soft soils impact the seismic performance of building frames under dynamic …
Published in Journal of Geotechnical Engineering · Vol. 12, Issue 2, 2025 · pp. 25–27 Read article
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Unraveling Mixed Ionic-Electronic Conduction in Lithium-Substituted Rubidium Tetra Titanates via Dielectric Spectroscopy and EPR Analysis
Abstract: Lithium-substituted Rubidium Tetra Titanates with varying concentrations of lithium carbonate (Li₂CO₃) — specifically 0.01, 0.05, and 0.1 molar percentages — were successfully synthesized using a conventional high-temperature solid-state reaction method. The resulting compounds follow the general chemical formula Rb₂₋ₓLiₓTi₄O₉. X-ray diffraction (XRD) analysis confirmed that lithium ions were successfully incorporated into the crystal lattice without disrupting the fundamental layered structure of the host material. The crystal system remained monoclinic across …
Published in Research & Reviews : Journal of Physics · Vol. 14, Issue 2, 2025 · pp. 19–29 Read article
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Elucidation of Physical Structural Stability of Nickel Nanoparticles Additive-Based Magnetorheological Grease
Abstract: This study investigates the influence of nickel nanoparticles on the physical properties and structural stability of magnetorheological grease (NMRG) as a smart composite. The incorporation of nickel nanoparticles aims to mitigate issues commonly observed in conventional magnetorheological grease (MRG), including particle aggregation within the fibrous matrix, limited material performance, and deformation instability. NMRG samples containing 1–5 wt% nickel nanoparticles were prepared using a mechanical stirring method. The tests focused on …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 191–215 Read article
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Green Synthesis and Functional Evaluation of Ag–Polypyrrole/TeO2 Nanocomposites for Advanced Electronic Applications
Abstract: Ag–PPy/TeO₂ nanocomposites with TeO₂ loadings ranging from 2% to 10% were synthesized using an in-situ chemical polymerization method. Green tea extract, rich in phytochemicals, acted as both a reducing and stabilizing agent to facilitate the formation of metal oxide nanoparticles. The structural and morphological characteristics of the nanocomposites were analyzed using FTIR, PXRD, and SEM techniques. FTIR confirmed the successful integration of Ag, TeO₂, and PPy functional groups. PXRD patterns …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 64–76 Read article
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Characterization and Performance of a Multiphase Lignocellulosic-Polymeric Composite Growth Media in an IoT-Automated NFT Hydroponic System
Abstract: Hydroponics utilizing the Nutrient Film Technique (NFT) entails a type of soilless agriculture involving the delivery of a continuously flowing and thin film of nutrient-filled solution onto the roots of plants. With the move toward sustainable and efficient urban agriculture in the contemporary world and need to produce more effective and resource-efficient solutions, there have been significant efforts aimed at improving these techniques through advanced materials and automation. A consistent …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 542–555 Read article
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Optimization of Machining Parameters of EN-27 Material Using Wire Electric Discharge Machining (WEDM)
Abstract: The optimization of Wire Electrical Discharge Machining (WEDM) parameters for EN-27 alloy steel, a high-strength material widely utilized in mechanical and structural applications, is the subject of this study's methodical analysis. Due to its hardness and poor machinability by conventional methods, WEDM is preferred for achieving precise dimensional accuracy and surface integrity. The primary objective of this work is to enhance machining performance by identifying optimal process parameters influencing Material …
Published in Journal of Production Research & Management · Vol. 16, Issue 1, 2026 · pp. 32–36 Read article
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Optimized Machine Learning Framework for Battery State Prediction in Smart Charging Systems
Abstract: Good estimation of battery states, including State-of-Charge (SoC), State-of-Health (SoH), and Remaining Useful Life (RUL), are important in managing energy wisely and controlling the adaptive charging. This work introduces a streamlined machine learning model based on the ability to use multi-dimensional sensor measurements in terms of voltage, current, temperature, and cycle number to forecast battery conditions with high accuracy. Decent preprocessing, such as noise elimination, feature scaling, and calculated features, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 11–23 Read article
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Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Abstract: Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance. This study proposes a Hybrid Quantum-Classical Reinforcement Learning (HQCRL) Enabled Thermal-Aware EDA Framework for next-generation energy- efficient VLSI systems. The proposed framework integrates quantum-inspired optimization techniques with classical reinforcement learning algorithms to address the challenges of placement, routing, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 Read article
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Enhancing Chatter Resistance in Deep Hole Boring Through Modified Tool Design: A Study on Impact of Length-To-Diameter (L/D) Ratio
Abstract: Deep hole boring is a specialized machining process crucial for creating precise bores with high length-to-diameter (L/D) ratios, particularly vital in aerospace, automotive, and oil and gas industries. The L/D ratio is pivotal for stability and performance. Chatter, a detrimental vibration phenomenon, is a significant concern in deep hole boring, influenced by the L/D ratio. Higher L/D ratios increase chatter, leading to poor surface finish and reduced tool life. Longer …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 2, Issue 2, 2024 · pp. 24–33 Read article
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A Critical Review of the Limitations of the Arithmetic Mean and the Robustness of the Median in Statistical Analysis
Abstract: Arithmetic mean is an extremely popular measure of central tendency used in statistical analyses, primarily because it is so easy to calculate and has many positive mathematical characteristics. However, when there are outliers, skewed distributions or heterogeneous spread of data, the reliability of the arithmetic mean diminishes greatly. This paper includes a critical review of the limitations of the arithmetic mean and an assessment of the robustness of the median …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 16, Issue 2, 2026 Read article
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Advancement in Biodegradable Equipment for Flexible and Sustainable Electronics
Abstract: Biodegradable electronics are a quickly developing area focused on reducing the environmental impact of traditional electronic waste by using materials that can break down naturally after use. These devices use eco-friendly polymers, nanocomposites, and bio-based materials that maintain electrical function temporarily before safely decomposing. Recent developments show the potential of plant-based polymers, conductive biodegradable composites, and transient materials that support flexible and wearable applications without causing long-term harm to the …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 2, 2025 · pp. 32–37 Read article
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Advanced Anomaly Detection in Cloud Infrastructures Using Deep Learning Algorithms
Abstract: It is critical to guarantee the stability and security of cloud environments as cloud computing is becoming the backbone of contemporary IT infrastructures. Neglecting to quickly identify and resolve anomalies, which might point to security breaches, performance problems, or system breakdowns, can lead to disastrous outcomes. The increasing size and complexity of cloud infrastructures are challenging the effectiveness of traditional anomaly detection methods. These approaches often depend on rule-based systems …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 1–11 Read article
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Structure–Optical Property Correlation of Co-Doped TiO₂ and ZnO Nanofillers for Advanced Functional Composite Applications
Abstract: This study investigates the enhancement of the structural and optical properties of titanium dioxide (TiO₂) and zinc oxide (ZnO) nanoparticles through cobalt (Co) doping. Pristine TiO₂ and ZnO are widely studied metal oxides; however, their large band gaps and limited visible-light absorption restrict their performance in optoelectronic, photocatalytic, and environmental applications. Co doping is employed as an effective strategy to overcome these limitations by inducing band-gap narrowing, creating defect-related electronic …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1374–1394 Read article
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Understanding Sentiment Trends Through Zero-Shot and Few-Shot Learning Models
Abstract: The requirement for large, manually labeled datasets is one of the main barriers to applying sentiment analysis algorithms in specialized or rapidly evolving disciplines in the present natural language processing (NLP) landscape. This work investigates a paradigm shift from traditional fully supervised learning to data-efficient methods, specifically zero-shot learning (ZSL) and few-shot learning (FSL). This study uses the advanced capabilities of instruction-tuned large language models (LLMs), like GPT-4, to assess …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 01–08 Read article
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Formation and Fabrication of A 3D- Printed Polymer Propeller for Improved Propulsion and Minimal Acoustic Emission: A Comparative Study for Small Unmanned Vehicles
Abstract: The current research focuses on a comparative analysis of propeller designs to identify an option that enhances thrust efficiency while minimizing acoustic noise. The study evaluates three distinct types of propellers: the traditional three-blade propeller, the Sharrow propeller, and a novel aero propeller featuring an air foil-shaped cross-section. To facilitate a hands-on analysis, these propellers were produced using 3D printing technology, specifically employing ABS filament through a Fused Deposition Modelling …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 252–261 Read article
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Natural Frequency Analysis of Polymer Composites
Abstract: Polymer composite materials are increasingly utilized in vibration-sensitive engineering applications due to their high strength-to-weight ratio, design flexibility, and tailorable dynamic properties. Among these properties, natural frequency plays a crucial role in determining structural stability, resonance avoidance, and dynamic performance. This review presents a comprehensive synthesis of recent research on the natural frequency characteristics of polymer composite structures, with emphasis on material properties, structural configurations, boundary conditions, damage effects, environmental …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 541–553 Read article
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Oceanmind Systems: AI-Driven Marine Life Intelligence for Climate Prediction and Ocean Ecosystem Stability
Abstract: Oceans regulate global climate systems, support biodiversity, and serve as critical carbon sinks, yet they remain under-monitored relative to their ecological importance. Traditional oceanographic methods rely heavily on satellite sensing, buoy networks, and periodic marine surveys, which often fail to capture real-time biological dynamics at micro-ecosystem levels. This paper introduces OceanMind Systems, an artificial intelligence (AI)-driven marine intelligence framework that integrates marine life behavior, oceanographic data, and computational modeling to …
Published in International Journal of Marine Life · Vol. 3, Issue 2, 2026 Read article
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
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Estimation of Alogliptin and Dapagliflozin in Synthetic Mixture by RP-HPLC Method
Abstract: The primary objective of the proposed research was to develop and validate analytical methods for the simultaneous quantification of Alogliptin and Dapagliflozin in a synthetic mixture. Alogliptin and Dapagliflozin are medications used for managing diabetes, with Alogliptin inhibiting the enzyme Dipeptidyl peptidase-4 and Dapagliflozin belonging to the class of sodium-glucose cotransporter 2 inhibitors. High-performance liquid chromatography method development was conducted using a C18 column (250 mmX4.6 mm, 5 μm particle …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 37–46 Read article
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Sustainable High-Strength Geopolymer Composite Reinforced with Nano-Silica and Basalt Fibers: Mechanical and Microstructural Evaluation
Abstract: Sustainable soil composites (SSC) were formulated by incorporating red earth with varying proportions of bagasse ash (BA) and hydrated lime to enhance geotechnical performance and promote the reuse of agro-industrial waste. Red earth served as the primary structural matrix, BA functioned as a pozzolanic filler, and lime acted as a chemical stabilizer. BA content ranged from 0% to 60%, identifying 10% as the optimum level for significant improvement, and lime …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1113–1122 Read article