Search
1986 articles for “failure-prediction AUROC of 0.967” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
Nothing matched all of your words, so these match any of them.
-
Optimizing Parameters for Dry Sliding Wear Control in Stir-Cast AA7050/SiC Composites
Abstract: Using a pin-on-disc tribometer, this study examined the dry sliding wear behavior of AA7050/SiC composites. The production of this metal matrix composite was achieved through the stir-casting process, which involved an initial step of melting the AA7050 alloy, followed by the careful introduction of silicon carbide (SiC) particles, stirring to achieve uniform dispersion, and finally, casting the molten mixture. Wear rate (WR) was determined by three operational parameters: SiC reinforcement …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1624–1635 Read article
-
Turning the Properties of Wastes Paper-Derived Cellulose Nanocrystals for Enhanced Erythromycin Adsorption
Abstract: This study explores the modification, characterization, and adsorption performance of waste paper-derived cellulose nanocrystals (CNCs) for the removal of erythromycin from aqueous solutions. CNCs were modified using organic acid, inorganic acid, and base treatments, and their structural changes were evaluated using FTIR, XRD, and BET analysis. FTIR confirmed the introduction of carboxyl and hydroxyl groups in acid-treated CNCs and deprotonation effects in base-treated CNCs. XRD analysis revealed that organic acid …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 1, 2026 · pp. 1–24 Read article
-
Study of Thermal Conductivity and Hardness of Coir Fiber Reinforced Epoxy Composite
Abstract: Researchers are drawn to polymer reinforced natural fibers composite for the development of new materials. The research aims to use waste fibers, specifically coir, to create polymer composite materials. Thermal conductivity and hardness of the composite results are determined under various conditions. Coir fiber is used as the reinforcement material and Coir powder is used as the filler material in the study. In the case of the matrix, the epoxy …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1576–1582 Read article
-
Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 45–54 Read article
-
Integrated Assessment of Soil Health Through Macronutrient Status and Physico-Chemical Properties in Selected Agricultural Blocks of Kangra District, Himachal Pradesh, India
Abstract: Soil health is a critical determinant of agricultural sustainability, particularly in ecologically sensitive Himalayan regions where intensive cultivation and heterogeneous landscapes influence nutrient dynamics. Balanced macronutrient availability, together with favourable physico-chemical properties, governs crop productivity, soil resilience, and long-term ecosystem functioning. Despite the agronomic importance of Kangra District (Himachal Pradesh), localized assessments integrating nutrient status with physico-chemical indicators across representative agricultural blocks remain limited. This study aimed to evaluate soil …
Published in Research & Reviews : Journal of Ecology · Vol. 15, Issue 1, 2026 · pp. 27–33 Read article
-
Particle Swarm Optimization Framework for Accurate Battery State-of-Charge and Remaining Useful Life Estimation
Abstract: Accurate estimation of the State of Charge (SOC) and State of Health (SOH) of a battery is key to safe and efficient management of batteries in electric vehicles and energy-storage systems. However, it is challenging due to high nonlinearity, varying operating conditions, measurement noise, and limited access to comprehensive electrochemical parameters. Traditional data-driven models often generalize poorly and require heavy tuning, which can produce unstable predictions. To address these problems, …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 53–64 Read article
-
Development of Biodegradable Poly (Lactic-Co-Glycolic Acid) (PLGA) Nanoparticles for Sustained Release of Insulin
Abstract: This research outlines the creation of biodegradable composite nanoparticles made from poly (lactic-co-glycolic acid) (PLGA) designed for the sustained release of insulin. The emphasis is on the interactions between the polymer and the drug at the interface, along with the dynamics of the release matrix. The in vitro release kinetics, surface morphology, encapsulation efficiency, particle size, and polydispersity of insulin-loaded PLGA nanoparticles were analyzed following their production via a double …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1690–1699 Read article
-
Process Optimization of Spot Welding for Galvanized Automotive Steel Sheets
Abstract: Resistance Spot Welding (RSW) is a pillar of the modern automotive industry with the usage of lightweight and high-strength products at the highest point of demand. The optimum weld quality of galvanized steel sheets which is a material of choice because of its additional corrosion protective property is however not achieved easily. This study is a well-developed data-based solution to designing the RSW process in the most efficient way, providing …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 32–42 Read article
-
Biopolymer–Cement Hybrid Panels from Recycled Paper Mill Reject: Experimental Characterisation and Machine Learning Optimization
Abstract: The increased rate of the accumulation of industrial residues in the developing countries is a major cause of concern for the environment. The current study brings forth the use of industrial residues in the form of the production of eco-friendly building materials as a sustainable approach to their valorization. The valorization of recycled paper mill reject, a cellulose-based biopolymeric industrial residue, is being addressed in this study as a reinforcement …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 67–90 Read article
-
Diabetes Risk & Al Nutrition Assistant
Abstract: The rising prevalence of diabetes mellitus has emerged as a major global health challenge. Early identification of individuals at risk, combined with personalized lifestyle-based interventions, can significantly reduce future complications. This study presents an AI-driven Nutrition Assistant integrated with a Diabetes Risk Prediction model. The system uses a machine learning classification approach to estimate the likelihood of diabetes based on clinical and nutritional factors, including body mass index, glucose levels, …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 31–38 Read article
-
Comparative Analysis of Processing-Property Relationships in Metal and Polymer Matrix Composites: A Unified Statistical Framework for Hardness Characterization
Abstract: Composite materials, encompassing both metal matrix composites (MMCs) and polymer matrix composites (PMCs), exhibit complex processing-property relationships that fundamentally govern their mechanical performance across diverse applications. This study presents a unified statistical framework for analyzing hardness characteristics in composite systems, using aluminum-tungsten carbide (Al-WC) metal matrix composites as a representative model system while establishing connections to polymer matrix composite behavior. The investigation employed comprehensive processing parameter optimization, microstructural characterization, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 419–430 Read article
-
Autonomous Agentic AI for Adaptive Cure Optimization and Defect Prevention in Thermoset Polymer Composite Manufacturing
Abstract: Thermoset polymer composites occupy a central position in modern structural manufacturing, from aircraft fuselages to wind-turbine blades. Despite progress in resin chemistry and fiber architecture, the “cure process” that transforms compliant preforms into load-bearing structures remains difficult to manage. Manufacturers encounter ‘voids’, “interlaminar delaminations”, and “spring-back distortion” when curing complex or thick-section parts. The cause is not ignorance of the relevant physics, but rather that ‘temperature’, ‘chemistry’, ‘rheology’, and ‘mechanics’ …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 301–320 Read article
-
Evaluation of Mucoadhesive Polymers for Nasal Delivery of Herbal Bioactives
Abstract: A study assessed mucoadhesive polymers for intranasal herbal bioactive administration with higher residence time and mucosal permeability. Chitosan, Carbopol® 934P, and HPMC K15M were utilized to manufacture mucoadhesive nasal gels with standardized herbal bioactive fractions. Formulations were examined for pH, viscosity, spreadability, drug content, mucoadhesive strength, in-vitro release, ex-vivo penetration, and short-term stability. All formulations demonstrated a suitable pH for nasal usage and uniform drug content (97.48 ± 1.12% to …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1680–1689 Read article
-
AI-Designed Functionally Graded Polymer Composites for Multifunctional Thin Films
Abstract: The design of multifunctional polymer composite thin films requires simultaneous optimization of mechanical, optical, barrier, and thermal properties—objectives often in conflict when using conventional homogeneous materials. This study presents an artificial intelligence-driven framework for designing functionally graded material (FGM) architectures in polymer nanocomposite thin films. We integrated machine learning with physics-based modeling to optimize compositional gradients across film thickness, achieving superior performance compared to homogeneous and discrete multilayer alternatives. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1026–1041 Read article
-
Experimental Exploration of Crack and Damage Dynamics of Hybrid FRP Nano Composites
Abstract: Fiber-reinforced polymer (FRP) composites have become essential materials in modern engineering structures because of their excellent strength-to-weight ratio, corrosion resistance, and adaptability in design. Among different fracture modes, Mode I interlaminar fracture where cracks propagate under tensile opening stresses is one of the most critical forms of damage in layered composites. Since delamination occurs within the matrix-rich regions between plies, improving the matrix properties plays a key role in enhancing …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 220–232 Read article
-
Environmental Impact Assessment of Ocean Energy Converters Using Quantum Machine Learning
Abstract: The accelerating deployment of ocean energy converters (OECs) across tidal, wave, osmotic, and thermal domains necessitates rigorous, data-intensive environmental impact assessment (EIA) frameworks capable of modelling multi-stressor marine ecosystems in real time. Classical machine learning approaches, while operationally mature, encounter scalability bottlenecks and feature correlation limitations when applied to the high-dimensional, non-linear datasets characteristic of offshore monitoring networks. This paper presents a comprehensive quantum machine learning (QML) framework for the …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 1, 2026 · pp. 22–31 Read article
-
Integrative Structural-Functional Genomics of Fc and Fab: Precision Models for Monoclonal Antibody Stability and Anti-Aggregation Engineering
Abstract: Monoclonal antibodies (mAbs) represent the cornerstone of biotherapeutics, yet aggregation propensity compromises up to 50% of candidates during development, driven by Fab hypervariability and Fc vulnerabilities.(1,2) This review integrates functional genomics from OAS (4B+ sequences)(5) and structural databases (SAbDab: 10K+ structures)(6) with machine learning models achieving R=0.97 for SAP prediction.(11) We dissect biophysical mechanisms, benchmark predictive tools (DeepSP, ESM2), and engineering strategies (YTE, FW mutations) that enhance Tm by 5-10°C …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 1, 2026 Read article
-
On the link of global warming and cloudiness in mid hills of Himachal Himalayas, India
Abstract: The present study investigated the monthly, seasonal, and annual cloud cover variability over two stations in the mid hills sub-temperate subhumid zone of Himachal Pradesh, by using Pearson’s correlation coefficient, Mann-Kendall (MK), and Sen’s slope estimator test. Daily data on cloud cover, sunshine hours, maximum and minimum temperature, morning and evening relative humidity, evaporation and rainfall for the period of 22 years (2001–2022) were used in the investigation. In the …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 39–49 Read article
-
Forecasting Climate-Driven Healthcare Demand in Agricultural Regions: A Multi-Modal AI Approach
Abstract: The rapidly increasing instability of world climatic regimes has made past meteorological thresholds irrelevant, especially in the agricultural areas where monetary stability and well-being of humans are closely intertwined with an environmental situation. The more the frequency of 1 in every 1000-year events, i.e., heatwaves and catastrophic flooding increase, the greater the rural healthcare systems are in crisis, i.e., unable to predict a surge in demand because of data scarcity, …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 28–38 Read article
-
Machine Learning Optimization for VARTM Carbon Polymer Laminates
Abstract: Vacuum-assisted resin transfer moulding (VARTM) is a key low-cost, out-of-autoclave process for manufacturing large-scale carbon-fibre reinforced polymer (CFRP) laminates crucial to aerospace wings, wind-turbine blades, marine hulls, and automotive structures. Unpredictable resin flow often leads to voids, dry spots, and race-tracking defects, resulting in 27.9% scrap rates and lengthy, costly trial-and-error design cycles. Although surrogate models provide rapid impregnation predictions for simple flat-plate geometries, vision-based monitoring is limited to idealized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 229–245 Read article