Search
143 articles for “hybrid frameworks”
-
Aspect-Based Sentiment Analysis Using a Hybrid Approach with Dependency Parsing
Abstract: The rapid expansion of digital communication has resulted in an unprecedented volume of consumer-generated textual data across online reviews, social media platforms, forums, and e-commerce websites. Extracting meaningful insights from this data is increasingly important for organizations seeking to understand customer opinions, preferences, and behavioral trends. Despite significant advances in sentiment analysis, many existing approaches primarily focus on surface-level features and often overlook deeper syntactic and semantic relationships within text. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 01–09 Read article
-
Overview AI-Driven Antenna Technologies and Privacy- Preserving Methods for Next-Generation 6G Wireless Systems
Abstract: The next generation of wireless communications, 6G, will be built on the convergence of artificial intelligence (AI) and advanced antenna systems. AI-driven antennas are poised to address the unprecedented requirements for data rate, reliability, adaptability, and ubiquity in future networks. An overview of current advancements in AI-enabled antenna systems for 6G networks is provided in this study. From traditional base station deployments to distributed, cell-free, and user-centric frameworks, it examines …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 28–34 Read article
-
Preparation and Characterization of Clay-Based Hybrid Membranes for Antibacterial Biodegradable Polymer Wound Dressings
Abstract: Recent developments in the field of polymer chemistry have resulted into many new forms of Hybrid polymer. This has further revolutionized the application of polymer chemistry in numerous fields. In this research, we manufactured clay-based hybrid membrane by adding clay to the biodegradable matrix of chitosan polymer. It is widely known that microbial and pathogenic organisms are being responsible for wound hampering infections such as impetigo. They can spread in …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
PI and Fuzzy Logic Controller Based Analysis of Load Frequency Control for Thermal-nuclear Hybrid Energy Systems
Abstract: In this paper a two-area system: area-1, which has a thermal power plant, and area-2, which contains a nuclear power plant. By combining these domains, two area thermal-nuclear systems are developed in the MATLAB Simulink framework. To ensure the quality of power generated and to feed the load, generation should be raised in tandem with the growth in load demand, or the network should be connected. Using various controllers, LFC …
Published in Trends in Electrical Engineering · Vol. 14, Issue 1, 2024 · pp. 1–9 Read article
-
Layered Metal–Polymer Hybrid Laminates with Embedded Impact Sensors for Connected Automotive Panels
Abstract: The increasing demand for lightweight, intelligent, and structurally reliable automotive components has accelerated the development of multifunctional hybrid materials capable of simultaneously providing superior mechanical performance and real-time structural health monitoring. In this study, a novel layered metal-polymer hybrid laminate incorporating an embedded flexible impact sensor was developed for connected automotive panel applications. The laminate was fabricated using AA6061-T6 aluminum alloy face sheets and a thermoplastic polyurethane interlayer through hot-press …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
-
Signal Drift Compensation in Polymer-Based Wearable Biosensors Using Data Processing Techniques
Abstract: Polymer-based wearable biosensors have emerged as promising platforms for continuous physiological monitoring due to their mechanical flexibility, low operating voltage, and compatibility with soft biological interfaces. However, their long-term deployment remains challenging because of signal drift caused by polymer ageing, hydration–dehydration cycles, ionic trapping, and environmental variations. These effects introduce baseline fluctuations and sensitivity degradation, which compromise the reliability and interpretability of physiological measurements. This study proposes a data-processing–driven framework …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 197–207 Read article
-
Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
-
Cardiovascular Illness Detection and Categorization with Innovative Neural Networks
Abstract: Health-related problems are increasingly prevalent in modern-day societies and are significantly shaped by a multitude of factors encountered in everyday life. Among these, cardiovascular diseases have emerged as one of the primary causes of death on a global scale, posing serious challenges to public health systems. In response to this growing concern, the present study proposes a machine learning-based framework that is not only highly effective but also reliable and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 21–30 Read article
-
Heterosis in Plants
Abstract: It refers to hybrid vigor or heterosis; herein, the offspring expressed better traits than one or both parent lines. This most often manifests in crop breeding as increased yield in F1 hybrids compared with their parents. Developing high-yielding hybrid cultivars across a wider range of crops represents an important strategy for addressing future food security. However, conventional hybrid breeding approaches are fraught with significant challenges in many self-pollinating crops, such …
Published in Research & Reviews : Journal of Botany · Vol. 14, Issue 2, 2025 · pp. 21–31 Read article
-
Thermodynamic Optimization and Exergy-Based Performance Analysis of Hybrid Thermal Management Systems for Electric Vehicles
Abstract: The transition toward sustainable transportation has brought electric vehicles (EVs) to the forefront of modern engineering innovation. Despite their environmental benefits and improved energy efficiency, EVs face major thermal challenges that affect performance, safety, and durability. Efficient thermal management of batteries, power electronics, and electric drive systems is vital to ensure reliability under diverse operating conditions. This study presents a detailed thermodynamic optimization and exergy-based performance analysis of hybrid thermal …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 2, 2025 · pp. 19–23 Read article
-
Next-Generation Membrane Materials: Advances, Applications, and Challenges
Abstract: Advanced membrane materials are better than regular polymers because they are more selective, permeable, and stable. New developments in nanomaterials, composite membranes, and surface engineering are making it possible to do more with water purification, gas separation, biomedical applications, and energy systems. Membrane technologies have become important tools in many areas, including biomedicine, energy systems, gas separation, and water purification. Recent progress in material science has made it possible to …
Published in International Journal of Membranes · Vol. 2, Issue 2, 2025 · pp. 19–28 Read article
-
Hybrid Material Systems for Flexible Electronics Electro-Mechanical Performance and Future Prospects
Abstract: Flexible electronics are transforming the landscape of modern electronic systems, enabling devices that are lightweight, stretchable, and adaptable to complex surfaces. These technologies are particularly impactful in applications such as wearable health monitors, soft robotics, energy harvesting systems, and implantable biomedical devices. At the heart of this evolution are hybrid material systems—engineered composites that combine organic polymers and inorganic nanomaterials to achieve synergistic electro-mechanical properties. These materials address the limitations …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 7–12 Read article
-
Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
-
Physicochemical Transitions and Polymerization Dynamics in Multi-Generational Dentin Adhesives: A Critical Review of the Resin-Dentin Composite Interface
Abstract: Adhesive dentistry has undergone a transformative refinement over the past three decades, transitioning from technique-sensitive, multi-step etch-and-rinse protocols to streamlined universal formulations. This narrative review critically synthesizes evidence from thirty peer-reviewed investigations to evaluate the evolution of dentin bonding agents from the fourth through the eighth generations. The analysis places particular emphasis on the physicochemical dynamics of the resin-dentin interface, including interfacial bond strength metrics, marginal integrity, and microleakage behavior. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 209–228 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
-
Study of Proximity Points and Fixed Points
Abstract: This paper explores the concepts of proximity points and fixed points, which are fundamental in mathematical analysis and nonlinear functional analysis. Fixed-point theorems play a crucial role in optimization, game theory, differential equations, and dynamic systems. Proximity points, an extension of fixed points, provide a more generalized approach, allowing near-coincidence rather than exact identity. The study discusses classical fixed-point theorems, such as Banach’s contraction principle, Brouwer’s fixed-point theorem, and Schauder’s …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 28–31 Read article
-
Deep Learning-Enhanced Polymer-Based Wearable Biosensors for Continuous Health Tracking via IoT
Abstract: The rapid proliferation of wearable biosensor technologies has transformed approaches to real-time health monitoring, yet challenges persist in achieving both mechanical robustness and reliable, continuous data analytics in dynamic environments. Conventional polymer-based sensing systems often fall short due to limited signal fidelity, inadequate adaptive analytics, or insufficient integration with secure, low-latency IoT frameworks. Addressing these deficiencies, this work introduces a flexible, deep learning-enhanced wearable biosensor platform that combines a nanostructured …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 18–31 Read article
-
Hybrid Composite Behavior of Concrete-Filled Steel Tube (CFST) Columns: Review of Collapse Mechanisms and Polymer-Based Enhancements
Abstract: Concrete-Filled Steel Tube (CFST) columns are an advanced hybrid composite system where the steel tube's confinement and the concrete core's load capacity work together to improve structural performance. While commonly used in civil engineering, CFSTs can also be understood within the framework of composite materials, similar to polymer- and fiber-reinforced composites, in which interactions between phases determine strength, ductility, and failure modes. This review compiles experimental and numerical research on …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 78–97 Read article
-
Integrated Optimization of Solar Photovoltaic Systems Using Taguchi Method and Computational Fluid Dynamics for Enhanced Efficiency
Abstract: The transition to renewable energy demands efficient and reliable photovoltaic (PV) systems to meet rising global energy needs. This study presents an integrated optimization framework combining the Taguchi method and Computational Fluid Dynamics (CFD) to improve the thermal and electrical performance of solar PV systems. A structured experimental design using an L9 orthogonal array evaluates the influence of three key parameters—material type, panel thickness, and cooling mechanism—on system efficiency. Analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 10–25 Read article
-
Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article