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246 articles for “Hybrid model”
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Dielectric Elastomers in Actuation and Energy Applications: Material Behavior and Design Strategies
Abstract: Dielectric elastomers (DEs), a class of electroactive polymers, have attracted significant attention for their ability to undergo large, reversible deformations under electric stimulation. This unique capability makes them highly suitable for a range of actuation and energy harvesting applications, especially in the emerging fields of soft robotics, flexible electronics, artificial muscles, and sustainable power generation systems. DEs offer compelling advantages such as low weight, mechanical flexibility, high energy density, and …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 13–18 Read article
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A Review on AI and Machine Learning for Predictive Maintenance and FDD in RAC Systems
Abstract: The paper reviews the existing AI/ML methods first in the general context of predictive maintenance and FDD of RAC systems, then specifically focusing on granular cooling appliances. Perspectives and insights are provided on the reasons why potentially valuable models do not make it into practice more often, and where future research and development should be headed. New emerging topics for decision support systems to include domain knowledge and physics-based modeling …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 13, Issue 1, 2026 · pp. 15–25 Read article
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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
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Performance Evaluation of Kevlar-Sisal-S-Glass Hybrid Composites with Ceramic Fillers for Structural Applications
Abstract: This study examines the mechanical properties of hybrid composite laminates reinforced with Kevlar, sisal, and S-glass fibers, and incorporating ceramic fillers—silicon carbide (SiC) and aluminum oxide (Al2O3)—within an epoxy matrix. The hand lay-up method was utilized to produce the laminates, ensuring a uniform fiber stacking sequence and including 10% filler material. Two composite variations were synthesized: one incorporating SiC and the other Al₂O₃, and both underwent tensile, flexural, hardness, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Brain Tumor Detection by Aggregating Deep Learning and GAN Models for Faster MRI image Synthesis
Abstract: Brain tumors comprise a global health challenge that, in order to be treated and organized, need early and accurate diagnosis. Usually conducted through medical imaging, brain tumor detection techniques have problems of accuracy, efficiency, and confidentiality. Issues of limited datasets, strict privacy laws that provide restrictions on data sharing, and the necessity for specialized expertise on medical image analysis relegates modern methodologies to vulgar charades. For patient prognosis, treatment planning, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 45–53 Read article
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Real-Time Edge Detection Camera Module Using Discrete Taylor Transform and Heat Equation (PDE): An Applied Mathematical Approach
Abstract: In modern digital signal processing, the capability for denoising and smoothing in real time is very important in scientific, engineering, and industrial applications. This paper presents an efficient hybrid framework that merges two mathematically sound methods, namely, DTT and PDE defined as the Heat Equation, to robustly denoise a signal with minimal distortion. The model addresses one of the most challenging tasks in signal restoration, which maintains the fidelity of …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article
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Entangled Shields: Securing Digital Systems in the Quantum Cryptographic Revolution
Abstract: Quantum computing utilizing principles of superposition and entanglement is poised to revolutionize the computational landscape, presenting unprecedented challenges and opportunities across various disciplines. Among these, cryptography stands at the forefront due to its reliance on computational hardness assumptions, which Quantum algorithms, such as Grover’s and Shor’s, can efficiently exploit. This study explores theoretical foundations and practical applications of quantum-safe cryptographic primitives, such as lattice-based cryptography, hash-based signature schemes, code-based systems, …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 33–43 Read article
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Tri-Band Edge-Cut Rectangular Microstrip Patch Antenna on Composite Substrate for RF Energy Harvesting in IoT Networks
Abstract: The increasing use of Internet of Things devices underscores the pressing need for sustainable energy solutions, since traditional batteries necessitate regular replacement and constrain scalability. Radio frequency energy harvesting is a viable option; nonetheless, antenna design continues to provide a significant problem owing to the requirements for compactness, efficiency, and multi-band functionality. A hybrid composite substrate configuration combining FR4 (εr = 4.3) and RT Duroid (εr = 2.2) is employed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 867–883 Read article
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Computational Simulations in Drug Discovery: Modeling Protein Folding and Drug Binding
Abstract: Computational simulations have become essential tools in drug discovery, offering unprecedented insights into molecular behavior at the atomic level. These simulations, particularly in the domains of protein folding and drug binding, allow for the exploration of complex biological systems that are often difficult to study experimentally. Protein folding, a critical aspect of drug discovery, involves the transition of a polypeptide chain from an unfolded to a biologically active structure. Understanding …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 23–29 Read article
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Quantum-Inspired Neural Networks: Accelerating AI for Large-Scale Data Processing
Abstract: Recently, the world of artificial intelligence has been buzzing with exciting ideas inspired by quantum computing, especially when it comes to processing large amounts of data. Introducing the Quantum-Inspired Neural Network (QINN), a novel approach to conventional neural networks that blends concepts from quantum mechanics with machine learning techniques. Unlike typical networks that rely on neurons, QINNs utilize qubit-based representations, enabling them to perform computations in a more flexible and …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 12–17 Read article
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Investigation of Mechanical Properties of Banana, Linen and Their Hybrid Reinforced Composite Laminates in Adverse Condition and Analyze Using ML
Abstract: This research investigates the mechanical performance of composite laminates reinforced with banana and linen fibers, focusing on both individual and hybrid fiber combinations. The primary objective is to assess how these natural fiber composites behave under extreme environmental conditions, particularly high humidity and fluctuating temperatures, which are common in aerospace and automotive applications.Key mechanical properties—tensile strength, flexural strength, and impact resistance—are experimentally evaluated to assess the performance and long-term reliability …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 25–31 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Improving Indoor Room Air Conditioning Using PID Control
Abstract: Energy use in building air conditioning contributes significantly to power demand; therefore, in this work, we propose an improved methodology to achieve comfort conditions through PID control assistance. The project develops a mathematical model based on analytical heat transfer equations for comfort conditions by fulfilling the Fanger equation, considering environmental parameters (ambient temperature), metabolic rate, and people’s physical activity (internal heat generation) to reduce power consumption and improve energy efficiency. …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 1, 2025 · pp. 1–21 Read article
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Efficient Fault Detection in Power Transmission: A Review of Three-Phase Line Fault Detection with Hybrid Energy using MATLAB
Abstract: In urban regions, the density of power demand has significantly increased recently. Large-scale subterranean power cable installations are beginning to take the place of overhead transmission lines everywhere in the world because of environmental concerns in highly populated areas. The present project's primary objective is to use MATLAB to create a simulation model that includes 3ph symmetrical and unsymmetrical defects. Some have proven to be effective in detecting errors while …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 1, 2023 · pp. 42–47 Read article
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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
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Fraud Detection in Government Procurement Using Machine Learning
Abstract: Fraud represents a significant challenge in the realm of procurement, with estimates indicating that between 12 and 30% of global procurement budgets are lost to fraudulent activities (OECD, 2023). The pervasive nature of procurement fraud, which may encompass a range of deceptive practices such as bid rigging, invoice fraud, and procurement kickbacks, not only undermines the integrity of financial operations but also results in substantial losses for organizations. These losses …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 19–34 Read article
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A Systematic Literature Review on Security Challenges in Cloud–Edge Hybrid Systems
Abstract: Cloud–edge hybrid systems have become a key framework in today’s distributed computing landscape, combining fast, near-source data processing at the edge with the flexible scalability and resource richness of centralized cloud infrastructures. However, this in- tegration introduces a complex security landscape where tradi- tional perimeter- based cloud security measures are insufficient for resource- constrained and physically exposed edge nodes. This literature review synthesizes findings from established research publications (2020–2025), focusing …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 Read article
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Evaluation of Credit Risk of Bank Customers with a Hybrid Approach of Data Mining Techniques
Abstract: Credit risk poses the most significant threat to financial and monetary institutions. Banks strive to offer loans that generate high returns while minimizing risk. Achieving this requires the ability to accurately identify and classify credit customers, both individuals and legal entities, according to their likelihood of fully meeting their obligations. This classification is done using relevant financial and non-financial criteria. The primary goal of this study is to assess the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 63–81 Read article
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Next-Generation Biodegradable Polymer Composites: Enhancing Mechanical and Thermal Performance through Green Reinforcements
Abstract: Next-generation biodegradable polymer composites, combining compostable matrices such as polylactic acid (PLA), polyhydroxyalkanoates (PHAs) and starch-based polymers with green reinforcements (e.g., nanocellulose, lignin, agricultural residues and other bio-fillers), offer a pragmatic route to reconcile high performance with end-of-life sustainability. This paper examines recent advances in the design, processing and interfacial engineering of such composites to enhance mechanical stiffness, strength, toughness and thermal stability while preserving—or intentionally controlling—biodegradation pathways. Emphasis is …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1780–1794 Read article
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Path Lab-AI: An Autonomous Framework for Error-Free Histopathology Slide Interpretation
Abstract: Path Lab-AI represents a fully autonomous platform for the analysis of histopathology slides with circumscribed structures, designed to obtain highly accurate results using diagnostic methods and avoiding the usual limitations of standard microscopy-based pathology. Leveraging recent deep learning and whole slide image (WSI) analysis innovations, our system takes advantage of automated WSI ingestion along with pre-processing steps to account for staining variability, remove artifacts, and localize tissue from background. Such …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 19–30 Read article