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1916 articles for “Modeler” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Protective Effects of Phyllanthus amarus and Sida acuta Extracts Against DoxorubicinInduced Toxicity in Chick Embryo Models
Abstract: Chemotherapy remains a cornerstone of cancer treatment, yet severe side effects, including cardiotoxicity often limit its clinical application. Doxorubicin, a widely used anticancer drug, is particularly associated with dose-dependent toxicities that impact the heart, liver, and kidneys. In search of complementary approaches to mitigate these adverse effects, this study evaluates the protective potential of hydro-alcoholic extracts from Phyllanthus amarus and Sida acuta, two medicinal plants with known antioxidant and anti-inflammatory …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 2, 2025 Read article
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Integrating Building Information Modelling in the Pursuit of Sustainability: A Systematic Review
Abstract: Building Information Modelling (BIM) technologies drive sustainable practices throughout the project lifecycle. It highlights how BIM serves as a powerful tool for enhancing project efficiency, reducing waste, and improving resource management. Study different phases of implementation of BIM in sustainable development. Role of BIM in Energy efficiency, Waste management, Carbon footprint reduction, Water conservation and Project life cycle management. The paper reviews various studies that demonstrate the integration of BIM …
Published in Journal of Construction Engineering, Technology & Management · Vol. 15, Issue 3, 2025 · pp. 76–92 Read article
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A Combined ECG and PPG Signal Powered Artificial Intelligence-Based Prediction Model for Stroke
Abstract: Stroke is one of the most common causes of morbidity and mortality around the world, and emphasis on prevention and early detection strategies cannot be overstated. This review aims to integrate techniques of artificial intelligence with electrocardiogram and photoplethysmogram signals to enhance stroke prediction and monitoring of cardiovascular health. All in all, the application of artificial intelligence that incorporates machine learning, deep learning, or hybrid models gives robust tools toward …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 18–26 Read article
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Modelling and Analysis of Morphing Wing Structure for Variable Camber
Abstract: This study explores the modelling and analysis of a morphing wing with variable camber configurations to observe its aerodynamic characteristics compared to conventional form. The morphing wing is the concept where the shape of the wing is altered mid-flight based on different phases of flight to improve its aerodynamic characteristics. Morphing wing structure designs such as the corrugated and FISHBAC designs were considered for this analysis. The NACA 2412 airfoil …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 209–224 Read article
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Leveraging Large Language Models for Personalized Document Summarization and Question Answering: An Architecture for Stoner-Friendly Chatbots
Abstract: This study presents a detailed framework for developing personalized chatbots that utilize large language models (LLMs) to process and extract information from extensive documents while effectively responding to user inquiries. The proposed system is designed to mitigate information overload by employing advanced natural language processing techniques, leveraging technologies such as OpenAI, LangChain, and Streamlit. By integrating these tools, the framework enhances knowledge retrieval, simplifies document comprehension, and improves overall productivity. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 88–93 Read article
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Generative AI for VR: Creating Physically Realistic Models
Abstract: Virtual Reality has revolutionized the traditional learning system by creating and interactive and engaging environment. However, its ability to show precise real-world experiences is limited due to lack of physical realism. This study investigates the potential of Generative Adversarial Network (GAN) in creating physically realistic 3D models. Proposed system incorporates deep learning techniques along with physics-based constraints to enhance model’s accuracy and usability. To achieve this, experiments were conducted on …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 3, 2025 · pp. 14–22 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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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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An Empirical Study of Hyperparameter Impact on Deep Learning Models for Cardamom Leaf Disease Classification
Abstract: Recent advancements in deep learning models like convolutional neural networks and self- attention mechanisms have achieved great success in the field of plant disease classification. This study investigates the efficacy of two pre-trained models, ConvNeXT-Tiny and Swin Transformer-Tiny, for leaf disease classification in cardamom using a publicly available dataset constituting three categories of leaves, namely Healthy, Colletotrichum Blight and Phyllosticta Leaf Spot. The effectiveness of the models highly depends on …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 48–60 Read article
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Kinematic and Dynamic Modelling of a 6-DOF Robotic Manipulator for Industrial Applications
Abstract: The rapid evolution of industrial automation has intensified the need for highly accurate, flexible, and intelligent robotic systems capable of operating in dynamic and demanding environments. Among these systems, six-degree-of-freedom (6-DOF) robotic manipulators have emerged as a versatile solution due to their superior dexterity, large workspace, and human-arm-like motion capabilities. This research focuses on the comprehensive kinematic and dynamic modelling of a 6-DOF robotic manipulator designed for various industrial tasks …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 27–32 Read article
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Hierarchical Computational Modeling of Physical Structure Across Quark, Nuclear, and Atomic Scales
Abstract: We present a modular, multi-scale computational framework that integrates physical modeling and visualization across quark, nuclear, and atomic scales within a unified pipeline. Developed to address the traditional fragmentation between sub-nucleonic, nuclear, and electronic representations, the system provides a continuous data flow and visualization bridge spanning from femtometers to ångströms. The framework consists of three primary modules: a particle-level module illustrating nucleons as confined quark-triplets with effective flux-tube geometries; a …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 1, 2026 · pp. 38–53 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 Read article
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Process Capability Optimization of Thermoplastic Polyurethane (TPU) Printed Parts in Fused Deposition Modeling Process
Abstract: Fused Deposition Modelling (FDM) 3D printing process requires precise printed dimensions with a special assessment of process parameters using Taguchi optimization methodology. The proposed research aims to determine the optimal parametric setting to maximize the process capability index of diametral deviation and roundness of product in 3D printing process of TPU (thermoplastic polyurethane). The input factors for printing TPU in this research include the extrusion temperature, cooling fan speed, infill …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1846–1864 Read article
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Hybrid Quantum–Machine Learning Framework for Nonlinear Rheological Modeling of Polymer and Composite Materials
Abstract: In polymer and composite materials, a major challenge lies in predicting their nonlinear rheological response, owing to complex multiscale interactions that are not captured by traditional constitutive laws or conventional machine learning approaches. In this study, a hybrid Quantum–Machine Learning (QML) model comprising Quantum Support Vector Machine (QSVM) and Quantum Neural Network (QNN) architectures is proposed for viscosity prediction without requiring any specific rheological equation. To train and test the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 · pp. 19–35 Read article
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Fluid Dynamics of a Stressed Freshwater Lens: Integrated Flow Modeling and Pathways for Material-Centric Interventions in Khadir Island, Gujarat
Abstract: This study applies principles of fluid dynamics and porous media mechanics to analyze the behavior and sustainability of the freshwater lens in Khadir Island, an arid sedimentary island in Gujarat, India. We develop an integrated fluid flow model that couples surface hydrology with aquifer dynamics to quantify recharge fluxes, extraction stresses, and hydraulic responses. Using 11-year hydro-meteorological data (2011–2021) and sectoral demand projections, we characterize the island’s water budget through …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 12–29 Read article
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Model United Nations as a Platform for Interdisciplinary Learning and Global Citizenship: A Report on GMC Conference 2026
Abstract: This article presents a detailed report on GMC Conference 2026, the 3rd National Edition of the annual Model United Nations (MUN) conference organised by the GECA MUN Club at Government College of Engineering, Aurangabad (Chhatrapati Sambhajinagar), Maharashtra, India. Held on 17–18 January 2026, the conference brought together 370 delegates from more than 20 institutions across approximately seven Indian states, deliberating across nine committees on a range of substantive international and …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 16, Issue 2, 2026 · pp. 12–20 Read article
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Review of Relevant Evapotranspiration Models for Estimating Reference Evapotranspiration
Abstract: The word evapotranspiration (ET) is a very pivotal component of the hydrological cycle, and it has a very crucial but accurate design and operation in terms of management of irrigation systems. Its evaluation by direct measurement using lysimeters, atmometers, energy balance or pan evaporimeter is not usually feasible because it is complex, expensive and time consuming. Therefore, relevant indirect methods such as FAO–56 Penman–Monteith (PM), Priestly Taylor (PT), Blaney–Morin Nigeria …
Published in Emerging Trends in Chemical Engineering · Vol. 9, Issue 1, 2022 · pp. 45–54 Read article
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Development of an Intelligent and Statistical Model for Prediction of Rock Mass Deformation Modulus
Abstract: The rock mass deformation modulus (Em) takes into account the plastic and the elastic deformation of the rock mass. It has been widely used for designing structures such as dams, tunnels, caverns, and mines, etc. Since the tests available for ascertaining Em are expensive and time consuming, several equations were suggested in the past. However, it has been found that the existing models are limited to specific type of rock …
Published in Journal of Geotechnical Engineering · Vol. 6, Issue 2, 2019 · pp. 39–50 Read article
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Interpretive Structural Modelling Apply to Green Supply Chain Management
Abstract: This study aims to investigate the green supply chain management (GSCM) practices likely to be adopted by the electronic industry of electronics products in India. The approach of the present research includes depth literature review about the current scenario of electronic industry in India and the relationship between GSCM practices and environmental performance. The electronics products industries in India were sampled for empirical study. The parameters were analyzed using “Interpretive …
Published in Journal of Industrial Safety Engineering · Vol. 2, Issue 1, 2015 · pp. 13–27 Read article
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Model Based Controller Design for Position Control of Servo Controlled Hydraulic Actuator against Air Entrainment
Abstract: Position control is important for numerous industrial and aircraft applications. Electro-hydraulic actuators are used for position control for advantages they provide over other actuation systems. The hydraulic fluid used for actuation, though desired to be incompressible, has some compressibility in practice. Entrainment of air in the fluid increases compressibility effect by reducing the effective bulk modulus. Reduced bulk modulus makes position control difficult. The paper studies the effect of effective …
Published in Journal of Mechatronics and Automation · Vol. 3, Issue 2, 2016 · pp. 25–35 Read article