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419 articles for “generative models”
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MediSense AI - Smart Health Analysis System
Abstract: MediSense AI is a revolutionary health analysis system that empowers users by transforming complex medical data into understandable insights. This platform utilizes advanced technologies, particularly natural language processing and machine learning, to make intricate medical terminologies accessible to individuals without a healthcare background. Leveraging Llama 3, a cutting-edge AI model developed by Meta AI, the system can analyze various forms of medical data, including the ability for users to upload …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 20–30 Read article
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A Technical Blueprint for AI-Driven Localization in 6G Mobile Networks
Abstract: The advent of sixth-generation (6G) wireless systems promises unprecedented spatial resolution, ultra-low-latency, and pervasive connectivity, turning mobile localization from a peripheral service into a core enabler of immersive extended reality (XR), autonomous logistics, and digital twins. Yet, the sheer scale of dense terahertz (THz) deployments, the stochastic nature of reconfigurable intelligent surfaces (RIS), and the dynamic interference landscape render traditional model-based positioning techniques inadequate. This work investigates how artificial intelligence …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 26–34 Read article
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Transcript Summarizer of YouTube Videos Using Deep Learning
Abstract: Transcriber Sum is a deep learning-based YouTube transcript summarization tool. It employs advanced machine learning techniques to automatically generate concise summaries of YouTube video transcripts, enabling users to quickly grasp the key content and insights of videos without the need to watch or read the entire transcript. This Transcriber Sum addresses the challenge of providing users with concise and informative summaries of video content by harnessing the power of deep …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 119–126 Read article
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Review on Machine Learning Techniques for Heart Failure Analysis in Health Industries
Abstract: There are few bodily components as crucial as the heart. It aids in the filtration and distribution of blood to every area of a body. The world's biggest cause of death is heart disease. It has been reported that symptoms include breathing difficulties, fast heartbeat, and chest discomfort. They analyze this data on a regular basis. This review begins with a brief introduction of cardiac disease and the present methods …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 1, 2024 · pp. 29–43 Read article
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A Sustainable and Green Prototyping Framework for Low-carbon and Resource-efficient Virtual Product Development
Abstract: The increasing emphasis on sustainable manufacturing has intensified the need for environmentally responsible design and development methodologies for polymer and polymer-composite materials, where material selection, processing routes, and waste generation play a critical role in overall environmental impact. This paper presents a Sustainable and Green Prototyping (SGP) framework that integrates Virtual Prototyping (VP), Life Cycle Assessment (LCA), and multi-objective optimization to systematically reduce carbon footprint, energy consumption, and material waste …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 459–471 Read article
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Privacy-preserving Multi-keyword Search in Multi-owner Setting Using Blockchain
Abstract: Searchable encryption (SE) has become an essential cryptographic technique, allowing users to securely search through encrypted data. However, most existing SE schemes rely on a single intermediary, such as a cloud server, leading to potential single-point failures, privacy breaches, and untrustworthy results. Many blockchain-based SE schemes have been proposed to address these issues. However, they frequently encounter difficulties such as supporting a multi-keyword, multi-owner model, ensuring query privacy, and maintaining …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 2, 2024 · pp. 12–18 Read article
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Website Usability Using AI
Abstract: This article introduces a comprehensive framework that leverages artificial intelligence (AI), automated tools, and APIs to enhance the evaluation of website usability. The proposed framework integrates AI-driven models with traditional usability assessment techniques to create a more dynamic and effective evaluation process. Specifically, it utilizes Google Lighthouse to conduct in-depth audits on website performance, search engine optimization (SEO), and accessibility. Additionally, chatbot APIs are incorporated to gather real-time user feedback, …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 2, 2025 · pp. 19–27 Read article
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Polymer Composite-Enhanced Anaerobic Digestion of Kitchen Waste for Optimised Biogas Production: Process Design, Parametric Study, and Simulation Analysis
Abstract: There is an urgent need for decentralised sustainable biogas production from organic waste due to the rising amount of food waste in cities. The application of polymer composite material including HDPE tanks, PVC pipes, and FRP secondary containment systems presents a promising option compared to conventional MS digester fabrication in terms of durability, excellent thermal insulation capability, light weight, and easier installation. This study explores the possibility of adopting a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 803–818 Read article
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Role of Beowulf Clusters in Next-Generation Military Applications: A Comprehensive Study
Abstract: Beowulf clusters, which utilize cost-effective commodity hardware combined with open-source software for parallel computing, have emerged as a viable and efficient solution for high-performance computing needs. This paper explores their growing relevance and practical applications in modern and future military technologies. Contemporary military operations increasingly rely on rapid data processing, real-time intelligence, high-fidelity simulations, and autonomous decision-making systems. Beowulf clusters offer scalable and adaptable computational power that supports these demands …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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Comparative Analysis of Pond Ash as a Partial Replacement of Sand as Subbase Material for Concrete Paver Block Hardstand sustaining storage of Bulk Cargo
Abstract: This work presents an industrial waste-derived subbase material that can take the place of conventional granular material for subbase in hardstand foundation construction. This industrial waste hugely deposited in the ash lagoons namely Pond Ash (PA) which is globally generated at an amount of 780 Metric Tons from thermal power plants annually ,as foundation material for hardstand construction, will not only help the cause of residual waste disposal problems but …
Published in Journal of Geotechnical Engineering · Vol. 12, Issue 3, 2025 · pp. 32–45 Read article
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Smart Service Solutions AI: AI-driven Multimodal Search for Home Appliance Support
Abstract: The global home appliance services market is projected to reach USD 1,203.11 billion by 2032, driven by smart household appliances. Essential services like installations, maintenance, and repairs ensure optimal performance and longevity, leading to higher customer satisfaction and loyalty. The service station partner ecosystem is crucial for ongoing support and profitability. However, challenges such as identifying the right manuals, finding relevant parts, and providing accurate instructions must be addressed to …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 27–43 Read article
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Designing an AI-Based Platform for Stock Market Prediction
Abstract: The AI-Based Platform for Stock Market Prediction is an advanced tool designed to forecast stock prices and market trends using artificial intelligence. This platform combines machine learning algorithms, real-time financial data, and sentiment analysis to provide investors with actionable insights. The platform uses advanced predictive techniques like Long Short-Term Memory (LSTM) networks and Gradient Boosting Machines to generate precise and reliable forecasts. Additionally, it incorporates interactive visualizations and portfolio optimization …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 14–19 Read article
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Designing Self-Optimizing Operating Systems: Information-Theoretic Approaches to Thread Scheduler Implementation
Abstract: Thread Level Scheduling (TLS) in multi-core and many-core processor environments represents a critical frontier in next-generation operating system design. As computing systems grow increasingly heterogeneous and concurrent, traditional scheduling strategies often rely on heuristics or localized resource metrics, frequently overlooking the deeper, quantifiable relationships and uncertainties inherent in complex concurrent workloads. This study explores the application of information-theoretic approaches, specifically entropy-based task allocation, mutual information-driven dependency analysis, and channel capacity-inspired …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 31–39 Read article
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Offloading Computation to the Cloud
Abstract: Mobile devices are increasingly relied upon for complex and resource-intensive applications such as real-time video processing, augmented reality, and machine learning. However, their limited computational power, storage capacity, and battery life pose significant challenges. Computation offloading to the cloud has emerged as a promising solution to overcome these limitations by transferring demanding tasks from mobile devices to remote cloud servers. This approach enables improved performance, reduced energy consumption, and enhanced …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 27–37 Read article
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Formulation Challenges in Long-acting Injectable Small Molecules: Emerging Strategies and Perspectives
Abstract: Long-acting injectable (LAI) formulations represent a transformative approach in pharmacotherapy, particularly for conditions demanding sustained drug exposure over weeks to months. Although biologics have dominated this space historically, the adaptation of LAI technology to small molecules presents a distinct and complex set of challenges rooted in physicochemical properties, manufacturing scalability, and regulatory expectations. This review systematically addresses the principal formulation barriers encountered in developing LAI small-molecule products, including aqueous solubility …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 13, Issue 2, 2026 Read article
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Database-Driven Energy Management in Electric Vehicles
Abstract: With the growing concern over environmental pollution, there is an increasing demand for sustainable and eco-friendly technologies. Among these, electric vehicles (EVs) have emerged as a promising alternative to conventional fossil-fuel-based transportation. However, as EV adoption accelerates, efficient energy management becomes critical to enhance vehicle performance, extend battery life, and ensure overall system reliability. This research presents a Database-Driven Energy Management System (DBEMS) that leverages real-time data from EV components …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 19–24 Read article
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NanoBioAI: Utilizing Python to Investigate Magnetocaloric Effects in Magnetotactic Bacteria and Optimized Conditions for Thermotherapy
Abstract: The study presented in the research work represents a multidisciplinary approach, integrating biology, nanotechnology, and artificial intelligence. It specifically highlights the use of python computational power to investigate magnetocaloric effect (MCE) in magnetotactic bacteria (MTB), a phenomenon yet to be fully understood, characterized by reversible heating and cooling effects induced by magnetic fields. MTB are unique in that they contain embedded magnetic nanoparticles ranging from 10–100 nm in diameters. These …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 122–131 Read article
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Optimization of Process Parameters for FDM Printed Tensile Test Specimens to Reduce Energy Consumption and CO2 Emission for Sustainable Manufacturing
Abstract: Three-Dimensional Printing (3D Printing) is one of the advanced manufacturing technologies which is being tremendously used in many fields because of its innovative applications. The concept of making a three-dimensional product by adding the material layer upon layer through Computer Aided Design (CAD) file data as input source is known as 3D Printing. Fused Deposition Modelling (FDM) is one of the leading technologies from all the available 3D Printing technologies, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 63–71 Read article
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Formulation and Evaluation of Transdermal Patch to Enhance Treatment of Alopecia
Abstract: The improvement of novel topical sedate conveyance frameworks has picked up noteworthy consideration due to their potential in upgrading the helpful viability and persistent compliance whereas minimizing systemic side impacts. This thinks about centers on the definition and assessment of transdermal patches planned to discharge allicin, the essential naturally dynamic compound determined from garlic (Allium sativum) extricate. Allicin is eminent for its wide range of pharmacological properties, counting antimicrobial, anti-inflammatory, …
Published in Trends in Drug Delivery · Vol. 12, Issue 2, 2025 · pp. 20–33 Read article
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Strategies for Efficient Integration of Distributed Energy Resources into Microgrid Systems
Abstract: With the growing integration of Distributed Energy Resources into modern power systems, the global energy landscape is changing. Some of the DERs are solar photovoltaic (PV), wind turbines, battery storage systems, combined heat and power (CHP) units, and electric vehicles (EVs). Some of the advantages include lower transmission losses, better energy efficiency, and more resilience to grid failures. However, the far-reaching integration of DERs carries with it considerable technical, economic, …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 51–56 Read article