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911 articles for “Integrated modeling”
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AI-Designed Functionally Graded Polymer Composites for Multifunctional Thin Films
Abstract: The design of multifunctional polymer composite thin films requires simultaneous optimization of mechanical, optical, barrier, and thermal properties—objectives often in conflict when using conventional homogeneous materials. This study presents an artificial intelligence-driven framework for designing functionally graded material (FGM) architectures in polymer nanocomposite thin films. We integrated machine learning with physics-based modeling to optimize compositional gradients across film thickness, achieving superior performance compared to homogeneous and discrete multilayer alternatives. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1026–1041 Read article
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Understanding the Capabilities of ChatGPT for Learning and AI-Powered Assessment
Abstract: This paper investigates the integration of ChatGPT, a generative AI language model developed by OpenAI, into modern educational environments with a focus on its role in learning and assessment. ChatGPT’s ability to understand and generate human- like responses positions it as a powerful tool for enhancing personalized learning experiences, supporting students through interactive tutoring, and assisting educators in administrative and academic tasks such as content creation and automated grading. The …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 101–107 Read article
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Enhancing Profanity Detection in Dravidian Languages: Leveraging Language Models for Optimization and Improvement
Abstract: Detecting and documenting instances of abusive behaviour can significantly improve the quality of virtual environments. Given the vast amount of content published daily on social media, it is impractical for human annotators to manually identify potentially harmful content. Recent algorithmic initiatives, especially on platforms like Twitter, have advanced in abuse detection. However, for Dravidian texts, there remains a need to understand the context better and build robust language models for …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 17–23 Read article
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Data-Driven Predictive Analytics and Decision- Making in FinTech Using MongoDB and High-Throughput Data Pipelines
Abstract: This paper examines the implementation of MongoDB and high-throughput data pipelines within the financial technology (FinTech) sector to drive data-informed predictive analytics and decision-making. The study focuses on the architectural components, scalability, and challenges of integrating NoSQL databases into real-time data ingestion and analytics pipelines. The transformative potential of these technologies in modern financial systems is highlighted through practical use cases such as fraud detection, credit scoring, and personalized financial …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 1–15 Read article
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Remote Sensing and GIS-Based Approaches for Soil Salinization Assessment: A Comprehensive Review
Abstract: Soil salinization, a critical environmental challenge, significantly impacts land productivity, agricultural yields, and contributes to desertification, particularly in arid and semi-arid regions. Early detection and effective management of soil salinity are essential for sustainable agriculture and land management. Remote sensing (RS) and geographic information systems (GIS) have emerged as indispensable tools for mapping, monitoring, and analyzing soil salinity over vast areas. RS provides multi-temporal and multi-spectral data that helps identify …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 3, 2024 · pp. 29–38 Read article
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Improved Cooling Effectiveness in Radiators and Heat Exchangers with Nanofluid-Based Technology
Abstract: This study discusses how the process of heat transfer in radiators and heat exchangers can be improved using nanofluids and analysis of computational fluid dynamics. These nanofluids comprise Al₂O₃ and ZnO dispersed in water-based ethylene glycol solutions, and graphene oxide dispersed in water-based solutions, and performance evaluation was done for the range of flow rates 180–420 l/h. And a 3D CAD model was created using the ANSYS Workbench. It was …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 1, 2025 · pp. 31–62 Read article
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A Comprehensive Review of CMOS Analog Circuit Design Techniques for Low-Power VLSI Systems
Abstract: CMOS analog circuit design plays a significant role in the development of modern low-power Very Large-Scale Integration (VLSI) systems used in wireless communication, biomedical devices, portable electronics, embedded systems, and Internet of Things (IoT) applications. Research on low-power CMOS analogue design methodologies has intensified because to the growing need for high-performance, small, and energy-efficient electronic products. However, reducing power consumption while maintaining signal accuracy, noise performance, stability, bandwidth, and overall …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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DOCSNAP: Integrating NLP and Computer Vision for Comprehensive Document Summarization
Abstract: Because of the exponential growth of digital content, sophisticated tools are required for effective data interpretation and administration.. This project harnesses the capabilities of the Gemini AI model developed by Google DeepMind to address the challenges of PDF summarization and image captioning. Gemini AI integrates cutting-edge algorithms, including transformer architectures, to process textual and visual data seamlessly. The project's system architecture involves modules for text and image extraction, with a …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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MentaLLaMA: Advancing Mental Health Insights with Instruction-Finetuned Large Language Models
Abstract: The growing prevalence of mental health challenges in contemporary society has highlighted the urgent need for advanced, interpretable, and reliable artificial intelligence solutions that can support mental health assessment and intervention. In response to this need, this research introduces a novel collection of open-source, instruction-tuned large language models (LLMs) specifically designed to facilitate transparent and accurate mental health evaluations. Leveraging a newly developed dataset, which integrates multiple tasks and diverse …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 08–15 Read article
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Sustainable Architecture for Rural Communities: The Tanzanian Family House Model
Abstract: Sustainable rural housing in East Africa must respond simultaneously to climatic stress, water scarcity, sanitation challenges, and socio-cultural practices. This article presents the Tanzanian Family House as a climate-responsive and resource-efficient housing model developed specifically for rural Tanzanian communities. The project integrates low embodied energy materials, passive environmental strategies, and decentralized infrastructure systems to create a durable and culturally grounded dwelling that can be constructed using local skills and materials. …
Published in International Journal of Rural and Regional Development · Vol. 4, Issue 1, 2026 · pp. 1–12 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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Footstep Power Generation Using Piezoelectric Materials: A Renewable Approach for Smart Infrastructure
Abstract: The rapid depletion of fossil fuels and the increasing global demand for sustainable energy have necessitated the development of decentralized energy harvesting systems. This paper presents a comprehensive study on footstep-based power generation using piezoelectric materials as a viable renewable energy solution for smart infrastructure. The proposed system converts mechanical energy generated from human locomotion into electrical energy using optimized piezoelectric transducer arrays integrated beneath floor tiles. The study covers …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 Read article
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Machine Learning for Finding Materials for Membranes
Abstract: Traditionally, finding and improving membrane materials has depended on trial-and-error experiments, which can take a long time, cost a lot of money, and only cover a small area. Recent improvements in machine learning (ML) have the potential to change the way membrane materials are designed by making it possible to make predictions about performance, selectivity, and stability based on data. ML algorithms can find hidden links between the structure, composition, …
Published in International Journal of Membranes · Vol. 3, Issue 1, 2026 · pp. 1–7 Read article
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Quality Dimensions of Open Access E-Journals in Library and Information Science: An Analytical Study
Abstract: The rapid growth of open access e-journals in Library and Information Science marks a significant transformation today. Open access journals provide unrestricted access to peer-reviewed research, enabling LIS professionals, researchers, and students worldwide to access required knowledge without subscription barriers. This study focuses on evaluating open access (OA) e-journals in Library and Information Science (LIS), with particular attention to their accessibility, quality, and scholarly impact. The main objectives of the …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 3, 2025 · pp. 52–68 Read article
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Zebra Fish Embryo Assay: A Wonderful Tool for Ecotoxicological Risk Assessment with Special Reference to Heavy Metals - An Overview
Abstract: In recent years, environmental pollution has become a pressing concern, prompting extensive research in aquatic ecotoxicology. With environmental degradation getting worse day by day, ecotoxicology research has gained a lot of attention. This area of study examines how biological communities in aquatic environments are affected by environmental contaminants. To unravel the toxicological mechanisms of these exogenous compounds, scientists turn to biological models. Several aquatic species, including zebrafish, toads, and big …
Published in International Journal of Toxins and Toxics · Vol. 2, Issue 2, 2025 · pp. 56–70 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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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Extending the Lifespan of Offshore Platforms: Vital Strategies for Durability
Abstract: This article explores the preventive measures for enhancing the durability and sustainability of aging offshore platforms, focusing on their evaluation, life extension, and potential repurposing. It begins by discussing diagnostic systems that assess structural integrity and safety, highlighting the importance of degradation models and neural networks in predicting corrosion effects on platform longevity. The paper then contrasts outdated Malaysian jacket platforms with emerging renewable energy solutions, particularly Ocean Thermal Energy …
Published in Journal of Petroleum Engineering & Technology · Vol. 14, Issue 3, 2024 · pp. 11–18 Read article
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From Space to Sea: Leveraging Satellite Technology for Monitoring Marine Debris
Abstract: Marine trash endangers ecosystems, so efficient detection is critical. This article describes a novel strategy for improving detection accuracy by integrating YOLOv7 instance segmentation with attention processes. Three models are evaluated: lightweight coordinate attention, the convolutional block attention module (CBAM) for spatial-channel focus, and the bottle neck transformer, which relies on self-attention. On an annotated satellite image dataset, CBAM has the greatest F1 scores in box recognition (77%) and mask …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 1, 2025 · pp. 1–9 Read article
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Remote Sensing and GIS-Based Approaches for Groundwater Contamination Assessment: A Comprehensive Review of Methods, Sources, and Emerging Trends
Abstract: Groundwater contamination poses a serious threat to sustainable water resources, especially in developing regions with limited monitoring infrastructure. This review provides an in-depth analysis of remote sensing (RS) and geographic information system (GIS) techniques applied to identify, monitor, and assess groundwater contamination. The study categorizes major sources of pollution, including industrial effluents, agricultural runoff, and geogenic inputs and examines how multispectral and hyperspectral satellite data contribute to indirect mapping of …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 39–49 Read article