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911 articles for “Integrated modeling”
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AI-Powered Multilingual Mental Health Chatbot with Personalized Voice and Text Support on Streamlit
Abstract: Mental health concerns are increasingly recognized as one of the most pressing global challenges, with millions of people struggling to access timely, affordable, and personalized support. Barriers such as stigma, lack of professional availability, language differences, and geographical limitations often prevent individuals from seeking help when they need it most. To address this critical gap, this study introduces MindMate, an AI-powered multilingual chatbot specifically designed to provide both text-based and …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 40–50 Read article
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Debris Flow Kinetics in Planetary Environments: A Systems Perspective
Abstract: Debris flow kinetics in planetary environments represent a critical intersection of geomorphology, fluid mechanics, and planetary science. These gravity-driven flow mixtures of solids, liquids, and gases play a key role in shaping planetary surfaces and recording environmental histories. This study adopts a systems perspective to analyze debris flow behavior across different planetary contexts, emphasizing the interconnected roles of material properties, energy transformations, and environmental forcing. By integrating rheological models with …
Published in International Journal of Universe · Vol. 1, Issue 2, 2025 · pp. 08–17 Read article
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Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 Read article
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Microalgae Based Wastewater Treatment: A Sustainable Approach
Abstract: The global water crisis and strict environmental policies demand advanced wastewater treatment techniques that combine pollution control with resource recovery. Microalgae-based wastewater treatment has emerged as a sustainable biotechnological solution that aligns with circular economy principles by simultaneously eliminating contaminants and producing valuable biomass that can be converted into useful products. This review paper provides an in- depth assessment of the application of microalgae in treating municipal, industrial, and agricultural …
Published in International Journal of Sustainability · Vol. 3, Issue 2, 2026 · pp. 1–15 Read article
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Quick Service: A Scalable Multi-Service Web Platform—A Microservices Approach for Seamless Integration
Abstract: This study proposes a model designed to save both time and cost for individuals seeking convenient access to a variety of services. In today’s fast-paced lifestyle, people often require quick and reliable solutions that can be tailored to their immediate needs. Our approach focuses on delivering multiple on-demand services that can cater to both individuals and businesses, ensuring that essential tasks are completed efficiently and on time in many emerging …
Published in Journal of Open Source Developments · Vol. 12, Issue 3, 2025 · pp. 26–45 Read article
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A Meta-Analysis of the Role of Serverless Computing Models in Modern e-Healthcare Systems
Abstract: The integration of serverless computing models in e-healthcare systems represents a paradigm shift in healthcare technology infrastructure. This meta-analysis examines the role, benefits, and challenges of serverless architectures in modern healthcare applications, focusing on studies published between 2019 and 2025. Serverless computing offers unprecedented scalability, cost-efficiency, and operational flexibility, making it particularly suited for healthcare applications handling variable workloads such as medical imaging processing, real-time patient monitoring, and electronic health …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 49–58 Read article
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Lip Reading: Transforming Speech to Text
Abstract: Lip reading, the ability to interpret spoken language by observing lip movements, is a valuable skill that can aid in various applications, particularly in enhancing speech recognition systems. This project explores the implementation of a deep learning-based lip-reading model to improve the accuracy and robustness of speech recognition in challenging environments, such as noisy or audio-limited settings. The proposed lip-reading system leverages Convolutional Neural Networks (CNNs) and Recurrent Neural Networks …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 23–33 Read article
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A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article
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Interpretable Skin Cancer Detection via Optimized CNN Models for Smart Healthcare Solutions
Abstract: Skin cancer is a common and potentially life-threatening condition, highlighting the importance of reliable and efficient diagnostic techniques. Recently, convolutional neural networks (CNNs) have demonstrated significant potential in automating the classification of skin cancer using thermoscopic images. Despite these advancements, the lack of interpretability in these models poses a barrier to their widespread use in clinical settings. In this study, we propose an interpretable CNN architecture optimized for skin cancer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 41–45 Read article
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Modelling and Control of Grid-Connected PV–Battery Hybrid System Using Dynamic Voltage Restorer for Enhanced Power Quality
Abstract: The integration of large-scale photovoltaic (PV) systems into modern power grids introduces significant challenges in maintaining power quality, including voltage sags, swells, and harmonics. To address these issues, this study presents a comprehensive modelling and control framework for a grid-connected PV–Battery hybrid system equipped with a Dynamic Voltage Restorer (DVR). The PV array is modelled using detailed mathematical equations, while the DC–DC converter incorporates advanced Maximum Power Point Tracking (MPPT) …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 43–58 Read article
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Review On BIM-Based (Revit+Robot Software) Comparative Wind Load Analysis of High-Rise RCC Buildings in Zone-III, IV and V
Abstract: Wind load is one of the most critical factors influencing the design and serviceability of high-rise reinforced concrete (RCC) buildings. As building height increases, wind-induced effects such as storey drift, lateral displacement, and structural stiffness become dominant design considerations. Numerous studies have been conducted using conventional and advanced techniques such as Finite Element Method (FEM), Computational Fluid Dynamics (CFD), and Building Information Modelling (BIM). However, limited research focuses on comparative …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 Read article
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Study of Social Trends Prediction Using AI
Abstract: AI (Artificial Intelligence) has fundamentally changed the ability to analyze social trends by using large datasets to develop predictions about human behavior, public sentiment, and global events. Using methodologies such as Natural Language Processing (NLP), Time-Series Forecasting, and Graph-Based Social Network Analysis, AI is able to find hidden correlations in a variety of available datasets, from social media to economic indicators to public records, and fundamentally changes decision-making based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 19–29 Read article
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Data-Driven Digital Twin Model for Real-Time Strength Estimation in Polymeric Materials
Abstract: The real-time prediction of mechanical properties in polymeric materials is essential for ensuring quality, consistency, and operational efficiency in modern manufacturing systems. As industrial processes become increasingly complex, traditional trial-and-error approaches to material characterization are no longer sufficient to meet the demands of high-throughput production environments. This study introduces a digital twin-integrated machine learning approach for the real-time estimation of tensile strength in polymeric materials by combining simulation-driven insights with …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 246–257 Read article
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Atmospheric Determinants of Feed, Fodder, and Forage Contamination in a Changing Climate: Emerging Challenges for Sustainable Livestock Production
Abstract: Feed, fodder, and forage contamination represents a growing constraint to sustainable livestock production under a changing climate. Atmospheric determinants such as rising temperature, altered precipitation patterns, increased humidity, elevated carbon dioxide concentration, and enhanced aerosol and pollutant loads are increasingly recognized as critical drivers of contamination risks across feed supply chains. These atmospheric factors directly and indirectly influence crop growth, fungal proliferation, mycotoxin biosynthesis, microbial survival, and the deposition of …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 1–14 Read article
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A Machine Learning-Based Non-Invasive System for Blood Group Prediction Using Fingerprint Biometrics
Abstract: The research is targeted at the creation of innovative solution "Fingerprint Based Blood Group Prediction" for instant, non-invasive blood group determination from analysis of finger impressions, a breakthrough possibility in emergency health care. Sophisticated machine learning can be employed to map fingerprint patterns to corresponding blood group information and overcome the current lack of a direct connection between the two. Integration of various technologies: employed React for frontend development, Flask …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 9–18 Read article
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Enhancing Security in Unified Software Architecture for Smart Computing IoT Devices via Mobile App Authentication Using Quantum-Based Encryption
Abstract: Security remains a critical concern in the landscape of smart computing for IoT devices, necessitating robust measures to safeguard sensitive data and user privacy. In this context, the utilization of quantum-based encryption presents a promising avenue to enhance security in unified software architecture. This study proposes a model aimed at fortifying the security of IoT devices by integrating mobile app authentication with quantum-based encryption techniques. The model leverages Quantum Key …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 41–48 Read article
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Advancements in Electromechanical Modeling for Energy Harvesting and Actuators in Robotics and Design Engineering
Abstract: This article examines the expanding field of electromechanical modeling, highlighting the integration of energy harvesting, actuator behavior, and magnetic/electromagnetic analyses in the design and production of electromechanical systems. It discusses the application of the Galerkin method for modeling intricate vibrations and torque generation, with a particular focus on its use in actuators for robotics and induction motors. Significant advancements in energy harvesting methods, especially those utilizing mechanical vibrations, have led …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 21–25 Read article
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Investigation of Robotic Transverse Twin-Wire GMAW for Large-Scale Wire-Arc Additive Manufacturing Applications
Abstract: Bulk metal additive manufacturing using wire-arc processes has gained significant attention for fabricating large-scale engineering components due to their high deposition rate and material efficiency. In this study, the feasibility and performance of robotic transverse twin-wire gas metal arc welding (GMAW) for bulk wire-arc additive manufacturing (WAAM) is systematically assessed. The research focuses on understanding arc stability, weld bead characteristics, and process–product relationships under high-deposition conditions. Welding current signals from …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 4, Issue 1, 2026 · pp. 36–50 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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Machine Learning-Based Approach for Heart Disease Prediction
Abstract: Heart disease is a significant global health challenge, with early diagnosis and prediction being essential for reducing mortality rates. Machine Learning (ML), an efficiently developing field within Artificial Intelligence, provides innovative methods for analyzing complex clinical data to predict heart disease. This review examines the basic machine learning techniques, data, and metrics used in cardiovascular disease prediction. It explores the role of supervised learning, such as decision trees and logistic …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 64–73 Read article