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143 articles for “hybrid frameworks”
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Thermal Stability and Impact Performance of Basalt–Carbon Hybrid Laminates in Polyimide–Phenolic Matrices
Abstract: The impact resistance and thermal stability of the advanced polymer composites are properties that are necessary for the components that are subjected to dynamic conditions, which show the overall reliability and service performance of the laminates applied in automotive structures, protective casings, etc. These properties prevent premature softening or breakdown during long-term exposure to heat. Impact resistance and thermal stability of composite laminates are studied based on fiber orientation and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 247–260 Read article
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Carbon Capture Technologies: Innovations, Challenges, and Environmental Implication
Abstract: This review work provides a comprehensive overview of carbon capture and storage (CCS) technologies, their status, and future directions. It examines various capture methods, including pre-combustion, post-combustion, oxyfuel combustion, and direct air capture, as well as emerging and hybrid technologies such as metal-organic frameworks, ionic liquids, and microencapsulation. The study discusses the limits of current technologies and attempts to point out innovations needed to ameliorate these challenges. It also explores …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 15, Issue 1, 2025 · pp. 7–18 Read article
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Entropy, Symmetry, and Data Fusion: Emerging Methods in Multi-Objective Decision- Making and Smart Systems
Abstract: In the era of intelligent technologies and data-driven systems, multi-objective decision-making (MODM) has become an essential aspect of managing complex environments such as smart cities, autonomous systems, and cyber-physical networks. As decision-making scenarios become increasingly dynamic and uncertain, there is a growing need for advanced methodologies that can handle diverse objectives, conflicting constraints, and incomplete information. This review highlights the emerging role of entropy, symmetry, and data fusion as foundational …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 44–49 Read article
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Assessment of Matrix Cracking and Fiber Breakage in Hybrid Composite Materials.
Abstract: Hybrid composite materials, combining two or more distinct fiber or matrix constituents, have emerged as advanced structural solutions for aerospace, automotive, marine, and civil engineering applications. However, their complex microstructure makes them susceptible to multiple interacting damage mechanisms, particularly matrix cracking and fiber breakage. This study provides a comprehensive assessment of these damage modes, emphasizing their initiation, evolution, and combined effects on the mechanical integrity of hybrid composites. Matrix cracking …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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A Comprehensive Study of various Multi-Area Hybrid Power Systems for Generation Control
Abstract: This paper is a detailed examination of multi-area hybrid power systems in the control of the generation taking into consideration the two area up to five area connected networks. As renewable energy sources are more and more integrated, and modern grids become more and more complex, the stability of the system itself and the frequency regulation have risen to a major issue. The study highlights the significance of Automatic Generation …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 28–42 Read article
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Machine Learning Pipelines: A Survey on Automation, Scalability, and Deployment Strategies
Abstract: Machine learning (ML) has become a critical enabler of intelligent applications across domains, requiring robust, efficient, and scalable deployment workflows. This review paper provides an in-depth overview of machine learning pipelines, emphasizing three key dimensions: automation, scalability, and deployment methodologies. It begins by exploring automation techniques that reduce manual effort in data ingestion, preprocessing, model selection, and hyperparameter tuning. Tools such as AutoML, TFX, and workflow orchestration platforms are examined …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article
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Machine Learning Framework for Optimizing Polymer–Metal Oxide Composites as Charge Selective Layers in Perovskite Solar Cells
Abstract: To achieve high-performance and stability of perovskite solar cells (PSCs), it was important to incorporate innovative interfacial materials to tune the balanced charge extraction, low recombination, and enhanced operational lifespan. On this note, polymer composites with metal oxides have been proposed as promising candidates as charge selective layers (CSLs), whereby they present a rare combination of tunable energy levels, improved film forming abilities, and better interface engineering capabilities. In this …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1073–1098 Read article
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Hybrid Best-Response Algorithms for Mobile Computing Offloading: A Comprehensive Review
Abstract: The exponential growth of mobile applications with intensive computational requirements has necessitated innovative offloading strategies in mobile computing ecosystems. This comprehensive review examines hybrid best-response offloading algorithms integrated with game-theoretic optimization frameworks to address resource allocation challenges in mobile edge computing (MEC) environments. The proliferation of Internet of Things (IoT) devices and bandwidth-intensive applications has created unprecedented demands on mobile network infrastructure, compelling researchers to develop sophisticated offloading mechanisms that …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 20–26 Read article
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Fractional Calculus-Based Analysis of Magneto-Thermal Nanofluid Flow Over Stretching and Shrinking Surfaces
Abstract: This study presents a comprehensive investigation of magneto-thermal hybrid nanofluid flow over stretching and shrinking surfaces using a fractional calculus framework to capture the memory and hereditary characteristics of complex fluid transport phenomena. The proposed model incorporates the effects of magnetic field intensity, thermal radiation, viscous dissipation, Brownian motion, and thermophoretic diffusion on the velocity and temperature distributions within the boundary layer region. A fractional-order derivative formulation is employed to …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 2, 2026 Read article
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Dual-Stream Deep Learning Framework for Brain CT Image Classification and Implications for Polymer Composite Neuro Implant Evaluation
Abstract: Early and accurate classification of brain CT images is critical for diagnosing conditions such as aneurysms, tumors, and related lesions. We present a dual-stream image-classification framework that fuses convolutional neural network (CNN) features with handcrafted Histogram of Oriented Gradients (HOG) descriptors to jointly capture global semantics and local textural cues. The pipeline begins with modality unification via pixel-wise averaging to form a fused input, which is then processed in parallel …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 172–179 Read article
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Optimizing Multi-Cloud Infrastructure: Advanced Bash-Based Automation for Automated Security Patching and Health Monitoring in Hybrid Linux Environments
Abstract: The proliferation of multi-cloud and hybrid Linux environments has introduced significant operational complexity, particularly in maintaining security compliance and system reliability across diverse infrastructure silos. Traditional patch management approaches, relying on manual interventions or disparate vendor-specific tools, suffer from latency, configuration drift, and limited visibility. This article presents a novel, lightweight automation framework constructed entirely in advanced Bash scripting to address automated security patching and real-time health monitoring across hybrid …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 2, 2026 Read article
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Data-Driven Life Prediction of Fiber-Reinforced Polymer Composites Using IoT Sensing and Machine Learning Algorithms
Abstract: The accurate prediction of fatigue life in fiber-reinforced polymer (FRP) composites remains a major challenge due to their nonlinear, multi-mechanism degradation behavior under variable loading conditions. This study presents a data-driven framework, H-LiProNet, which combines real-time IoT sensing with hybrid machine learning to estimate remaining useful life (RUL) in FRP composites. The proposed system integrates embedded Fiber Bragg Grating (FBG) and acoustic emission (AE) sensors to capture strain and damage …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 116–130 Read article
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Enhancing Solar Water Pumping in Arid Regions with Hybrid Super Capacitor and Battery Storage
Abstract: Water scarcity and unreliable grid electricity are two of the most pressing challenges facing rural communities in arid and semiarid regions. Standalone solar photovoltaic (PV) pumping systems have emerged as a clean, lowmaintenance alternative to dieselpowered pumps, yet their performance is constrained by the intermittent nature of sunlight and the limited energybuffering capacity of conventional batteries. This study investigates the integration of a highpower, highenergydensity supercapacitor bank as a hybrid …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 17–29 Read article
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LoRa and LoRaWAN in the IoT: Performance, Challenges, and Future Opportunities
Abstract: This paper provides a broad overview of both LoRa and LoRaWAN technologies in the context of Internet of Things (IoT). The market need for communication technology to be low-power and long-range continues to grow, and LoRa and LoRaWAN are emerging as viable options for enabling widespread IoT applications in a variety of applications. This review offers structured and comparative assessment of their functionality in different environments, such as urban, rural, …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 2, 2026 Read article
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AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 Read article
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Mathematical Modeling of Epidemics Using Stochastic Differential Equations: A Review
Abstract: The accurate modeling of infectious disease dynamics is crucial for predicting outbreaks and informing public health interventions. While deterministic models such as the SIR (Susceptible-Infected-Recovered) framework have traditionally been used to understand disease transmission, they often fail to account for the randomness inherent in real-world scenarios. Disease spread is influenced by numerous uncertain factors, including individual behavioral changes, environmental fluctuations, and imperfect data reporting. These uncertainties can significantly impact model …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 1–6 Read article
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A Hybrid Mathematical Model for Epidemic Outbreak Forecasting Using Machine Learning and Cloud Computing
Abstract: The increasing frequency of infectious disease outbreaks has emphasized the necessity for intelligent epidemic surveillance systems capable of predicting disease spread at an early stage. Conventional outbreak detection approaches rely heavily on delayed statistical reporting and manual monitoring techniques, resulting in reduced responsiveness during critical periods. This paper presents a mathematical predictive framework for epidemic outbreak detection using machine learning and cloud computing technologies. The proposed framework integrates the Susceptible–Infected–Recovered …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 01–06 Read article
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Performance Improvement of Standalone Solar PV Pumping System Using Supercapacitor
Abstract: Two of the most pressing issues when it comes to rural communities of arid and semi-arid regions are water shortage and unstable grid electricity. Standalone solar photovoltaic (PV) pumping systems have been introduced as a clean, low maintenance alternative to diesel powered pumps, but their performance is limited by intermittent nature of sunlight and limited energy buffering capacity of conventional batteries. The paper is an investigation into the incorporation of …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 54–62 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
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Graphene Based Electronic Skin for Wearable Health Monitoring and Human– review on Machine Interaction, Materials, Structures and AI Integration
Abstract: Graphene-based electronic skin (e-skin) has emerged as a transformative technology for next-generation wearable health monitoring and advanced human–machine interaction (HMI). Owing to its outstanding electrical conductivity, mechanical flexibility, atomic-scale thickness, and biocompatibility, graphene enables the fabrication of ultrathin, conformal, and multifunctional sensors capable of mimicking the sensory functions of natural human skin. Over the past decade, research in this domain has progressed rapidly across four interconnected fronts: material synthesis and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article