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246 articles for “hybrid modeling”
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Transforming Transportation in India: Exploring the Challenges and Opportunities of Electric Vehicles
Abstract: They also help lessen the impact of ozone-depleting substances and support the widespread adoption of renewable energy. Although significant research has focused on EV features, performance, and charging infrastructure, challenges in production and network modeling persist. This paper provides an overview of various EV technologies, including EVs, hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs), and evaluates their market penetration rates. It explores various …
Published in International Journal of Energy and Thermal Applications · Vol. 2, Issue 2, 2024 · pp. 17–23 Read article
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An Analysis of Graph Database in Data Modelling and Analysis for a Recommendation System
Abstract: This research work focuses on graph databases, mainly Neo4j databases, in recommendation systems for e-commerce websites. The importance of research is that it explains how graph databases efficiently handle the complex relationship between user-items, which is difficult for traditional databases. Sparsity, limited diversity, and high setup costs are the challenges traditional databases face. This research work overcomes these problems using Ne04j with Cypher query language and graph algorithms (PageRank, Shortest …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 33–39 Read article
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Effect of Drilling Process Parameters on Surface Roughness of LM6/B4C/Fly Ash Hybrid Composites
Abstract: This research seeks to assess the effect of process variables such as feed rate (FR), spindle speed (SS), drill material (DM) and reinforcement (R%) on surface roughness (SR) when drilling LM6/B4C/Fly ash hybrid composites. The stir casting process was used to fabricate the LM6/B4C/Flyash hybrid composites utilizing LM6 aluminum alloy as the matrix material and B4C/Fly ash as strengthening materials. Experiments were carried out using an L18 orthogonal array (OA) …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 898–906 Read article
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Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article
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A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data
Abstract: With the rise of social media platforms like Twitter, Reddit, and Facebook, individuals increasingly share personal information about their moods, behaviors, and mental states. This trend provides a unique opportunity to leverage large-scale textual data for understanding and monitoring mental health conditions, particularly depression, a prevalent and challenging mental health issue. Traditional depression assessments are often confined to clinical environments and lack the capacity for real-time monitoring. In contrast, social …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 55–65 Read article
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Enhancing Trust in Education Through Blockchain- Based Credential Authentication
Abstract: Academic credentials such as degree certificates, transcripts, and course completion records are fundamental for validating an individual’s educational achievements. However, conventional credential management systems largely rely on centralized databases and physical documentation, making them vulnerable to forgery, unauthorized modification, data loss, and inefficient verification processes. These limitations reduce trust among educational institutions, employers, and learners, while also increasing administrative overhead. This study proposes a blockchain-based credential authentication framework designed to …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 1–7 Read article
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Mechanical Performance Assessment of Hybrid FRP Laminates with Carbon Fiber Core Using Experimental and Numerical Approaches
Abstract: The high strength-to-weight ratio, corrosion resistance and design flexibility of Fiber-reinforced polymer (FRP) composites have attracted considerable attention in aerospace, automotive and structural applications. This work presents an experimental and finite element study on the tensile and flexural behavior of epoxy-based hybrid FRP laminates. Five laminate configurations were manufactured, including a unidirectional carbon fiber laminate and four hybrid laminates, Kevlar–Carbon–Kevlar (K/C/K), Glass–Carbon–Glass (G/C/G), Kevlar–Carbon–Glass (K/C/G), and Glass–Carbon–Kevlar (G/C/K). For all …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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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
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Super Ni 718 Machinability Investigation on Electrical Discharge Machining Using Hybrid Al 7(075+178) Electrode Under Abrasive Assisted Dielectric
Abstract: As aluminum alloy is the lightest metal and has the best mechanical qualities among metal, it has proven to be a perfect choice for strututal industry, particularly in the aerospace sector.7xxx alloys from the Al alloy family are widely used in aviation constructions due to their outstanding processing, welding efficiency, great specific strength & stiffness, and high toughness. The two aluminum alloys that are most frequently used in airplane structures …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1–17 Read article
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AI-Based Threat Detection in Cloud Platforms
Abstract: This research work delves into the transformative role AI has come to assume for enhanced threat detection in the cloud ecosystem. The conventional security frameworks, which form the basis for many architectures, are several steps behind actualizing the rapidly evolving cyber threat landscape, exposing critical weaknesses in the areas of accuracy, adaptability, and speed of response. Initially, the study sets forth the problems with the old-school approaches to threat detection …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 01–10 Read article
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Photonic-Assisted Spintronic Solid-State Switching Model for High-Speed Memory Devices
Abstract: The rapid advancement of high-speed computing and data-centric applications has intensified the demand for energy-efficient and ultra-fast memory technologies. This paper proposes a Photonic-Assisted Spintronic Solid-State Switching Model for next-generation high-speed memory devices. The proposed framework integrates photonic excitation mechanisms with spintronic switching dynamics to enhance data transfer speed, minimize switching delay, and reduce power dissipation in solid-state memory architectures. By combining optical pulse-assisted spin polarization with magnetic tunnel junction-based …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Image Processing and Deep CNN-based Automatic Liver Cancer Detection
Abstract: Liver cancer ranks among the leading causes of mortality for people worldwide. In the current situation, manually identifying the cancer tissue is a challenging and timeconsuming task. Treatment planning, response monitoring, tumor load assessment, and prediction are all made possible by the segmentation of liver lesions in CT scans. To address the current problem of liver cancer, the Hybridized Fully Convolutional Neural Network (HFCNN), which has been theoretically modeled, has …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 39–41 Read article
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Light-Matter Interactions in Molecular Photochemistry
Abstract: Molecular photochemistry explores the ways of molecules interaction with light, absorb photons, and excited‐state processes, and ultimately conversion of photon energy into chemical change. Core concepts of this innovative and relevant field are matter interaction like electronic, vibrational, and rotational transitions; non‐adiabatic couplings; energy & electron transfer; and light–matter coupling in weak and strong regimes. This article briefly surveys the multiplicity of these interactions, from the fundamentals of photon absorption …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 33–42 Read article
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Neuro-Fuzzy Control Systems: A Cross-Domain Review
Abstract: This paper presents a comprehensive review of the application of neuro-fuzzy control systems in various industries. Using the combined strengths of neural networks and fuzzy logic, neural-fuzzy control systems emerge as versatile tools to solve challenging control challenges It begins with clarifying the theoretical basis of neural fuzzy systems, and emphasizing their scalability, definition, and robustness. Specific examples in each domain highlight the effectiveness of neuro-fuzzy control in solving real …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 1, 2024 · pp. 29–38 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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A Review of AI-Based Intrusion Detection Systems for Mobile Ad Hoc Networks (MANETs)
Abstract: Mobile Ad Hoc Networks (MANETs) comprise wireless networks that lack any conventional infrastructure . Their chief features include highly changing network topologies, lack of centralized administration, and open nature of communication, which collectively result in making MANETs of the wireless kind very susceptible to a diverse range of cyber-attacks like blackhole, greyhole, wormhole, flooding, Sybil and denial-of-service (DoS) among others. Conventionally, Intrusion Detection Systems (IDS) relying on static rule-based methods …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Design and Computational Analysis of Hybrid Carbon Fiber-Enhanced Metal Matrix Composite Spur Gears
Abstract: The automobile industry has to find the alternative solution for steel grade gears to overcome the weight to high strength ratio and thermal consideration with high damping properties. This study describes the design, FEM analysis, and performance evaluation of three new hybrid composite spur gears: a monolithic carbon fiber/epoxy (80/20 weight percent) composite (A), and two hybrids with steel (B) and aluminum (C) matrices (64% CF, 21% Epoxy, 15% metal). …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 158–172 Read article
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High-Velocity Impact Response of CFRP and Hybrid Composites: A Comprehensive Review on Ballistic Resistance and Damage Mechanisms
Abstract: This review consolidates recent advances in the study of high-velocity impact response of carbon fiber reinforced polymer and hybrid composites. Carbon fiber reinforced polymer composites are widely applied in aerospace, automotive, and defense due to their high strength-to-weight ratio, stiffness, and durability. However, their susceptibility to impact damage such as delamination, matrix cracking, and fiber breakage limits their performance under dynamic loading. To overcome these challenges, researchers have explored reinforcement …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 100–122 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