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1242 articles for “Data integration”
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Real-Time Air Quality Prediction Using IoT-Integrated Polymer Sensors and Recurrent Neural Networks
Abstract: Real-time air quality monitoring remains a critical challenge in urban environments, where traditional sensor infrastructures often suffer from limited responsiveness, poor scalability, and high deployment costs. The increasing prevalence of NO₂ pollution, a key contributor to respiratory and cardiovascular ailments, demands advanced sensing platforms capable of both accurate detection and predictive inference. Existing methods either rely on rigid electronic sensors lacking adaptability or on statistical forecasting models that fail to …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 332–347 Read article
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Exploring Gelatin Film an Eco-Friendly Biomaterial: Synthesis, Characterization, and Environmental Applications
Abstract: This study explores the synthesis, characterization, and application of eco-friendly gelatin films, a sustainable and biodegradable biopolymer alternative to synthetic plastics. Synthesized via solution casting and characterized by UV-Vis spectroscopy, FTIR, and TGA, these films demonstrated excellent molecular integrity and thickness-dependent properties, with higher gelatin concentrations leading to thicker films and delayed solubility. The research highlights their significant potential in removing diverse environmental pollutants, including dyes (methylene blue, methyl orange), …
Published in Journal of Water Pollution & Purification Research · Vol. 13, Issue 1, 2026 · pp. 1–16 Read article
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A Critical Review on Measuring Accessibility of Multimodal Transport Systems in Indian Cities
Abstract: Measuring accessibility is crucial for evaluating the performance of multimodal transport systems in Indian cities. This review paper examines the methodologies, indicators, and applications of accessibility measurement in the context of developing countries, focusing on Indian urban areas. The paper discusses the challenges posed by data limitations, informal transport modes, and socioeconomic disparities, and highlights the need for adapting accessibility measures to the Indian context. Case studies from major Indian …
Published in Trends in Transport Engineering and Applications · Vol. 11, Issue 1, 2024 · pp. 1–9 Read article
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An Innovative AI-Integrated Approach for Identifying the Tensile Robustness of Polymeric Materials
Abstract: Polymeric materials have so many applications and character similar to flexibility, robustness and lightweight nature they are essential to a large variety of industries. Though, it is difficult to establish their tensile robustness appropriately, particularly in a variety of environmental situation. Provide a recommended Artificial Intelligence (AI)-integrated method to decide the issues of rapidly ascertaining the tensile robustness of the polymeric material. Using machine learning (ML), this study, predicted and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 90–97 Read article
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Future Skills for Librarians: Adapting to AI Innovations
Abstract: As artificial intelligence (AI) reshapes the landscape of information management, librarians' roles are rapidly altering. This essay delves into the fundamental abilities that librarians must develop in order to adapt to AI breakthroughs and effectively satisfy their communities' evolving demands. Key abilities mentioned include digital literacy, data management, critical thinking, user experience design, and instructional technology. The essay emphasises the significance of continual professional growth in keeping up with technology …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 1, 2025 · pp. 27–31 Read article
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AI in Pharmacy Automation: A Review of Innovations in Robotics, Their Ethical Implications, and Impact on Workflow and Workforce
Abstract: The pharmacy profession has witnessed a paradigm shift with the integration of robotics and artificial intelligence (AI) in automation. Traditional practices that relied heavily on manual dispensing, paper documentation, and technician labor are now being augmented or replaced by robotic dispensing systems, sterile compounding machines, and predictive AI algorithms. These innovations enhance safety, improve efficiency, and reduce errors, while also raising complex ethical questions related to workforce displacement, liability, and …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 17, Issue 1, 2026 · pp. 01–07 Read article
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The Heat of Competition: Assessing Climate Vulnerabilities and Adaptive Governance in Endurance, Winter, and Youth Sports
Abstract: Background: Climate change is fundamentally reshaping the environmental parameters of global sport, posing unprecedented risks to athlete health, safety, and performance. As rising temperatures, frequent extreme heat events, and deteriorating air quality become the new normal, athletic environments from community fields to elite international arenas face an existential threat. Purpose: This study provides an interdisciplinary synthesis of the multifaceted impacts of climate change on athletes, integrating evidence from sports medicine, …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 9–17 Read article
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VIKSIT BHARAT: Empowering Indians in the Area of Caring Society Culture for National Development
Abstract: This paper examines the vision of Viksit Bharat (Developed India) by focusing on the empowerment of citizens through the cultivation of a “Caring Society Culture.” It argues that sustainable national development in India must go beyond economic indicators and be rooted in societal values such as empathy, mutual respect, and collective responsibility. The study highlights the interplay between social responsibility and national growth, asserting that a society driven by compassion …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 3, 2025 · pp. 37–47 Read article
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Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
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Predictive Factors of Long-Term Sobriety: A Post-Discharge Outcome Study in Mangalore, Goa, and Vasai (2019–2023)
Abstract: Relapse following discharge remains a major challenge in addiction recovery, even with structured treatment protocols in rehabilitation centers. This study examines post-discharge outcomes from Kripa Foundation’s rehabilitation centers in Mangalore, Goa, and Vasai over a five-year period (2019–2023). A total of 100 patients were categorized into four behavioural outcome groups: Clean (Sober), Relapsed, R.I.P. (Deceased), and Unknown. The study aimed to identify demographic and behavioural predictors of sustained sobriety post-discharge. …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 29–44 Read article
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Raspberry Pi-based Self-driving Car Technologies: A Review of Hardware and Software Integration
Abstract: An assessment of the state, possibilities, and difficulties of self-driving car technology. Autonomous vehicles (AVs), also referred to as self-driving cars, are automobiles that can navigate and function without the need for human involvement. They make decisions, sense their environment, and traverse routes safely by combining sensors, cameras, radar, lidar, and sophisticated algorithms. The advancement of autonomous vehicles holds the capacity to completely transform the transportation sector by enhancing security, …
Published in International Journal of Electronics Automation · Vol. 2, Issue 2, 2024 · pp. 1–6 Read article
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Renewable Solar Energy Prediction in India : 2025-2030
Abstract: As India endeavors to realize its objective of achieving 500 GW of renewable energy capacity by the year 2030, the precise forecasting of solar power generation is rendered increasingly essential. This scholarly article conducts a comprehensive review of the utilization of machine learning (ML) methodologies in the prediction of solar energy across diverse Indian states, underscoring their potential to address the complexities associated with the variability of solar irradiance. Conventional …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 3, 2024 · pp. 41–46 Read article
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Developing Techniques for Controlling Different Aspects of Text Generation Such as Tone and Contents
Abstract: Large Language Models (LLMs) have shown excellent text creation quality in Natural Language Processing (NLP). However, LLMs have to satisfy ever-more-complex standards in real-world applications. LLMs are supposed to meet specific user goals, like as mimicking specific writing styles or producing material with poetic richness, in addition to eliminating inaccurate or objectionable content. Controllable Text Generation (CTG) techniques were developed in response to these diverse demands. They guarantee that outputs …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 34–39 Read article
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RTL-to-GDSII Flow Optimization for Low-Power 32-bit RISC-V Processor
Abstract: This paper presents the implementation and optimization of a 32-bit RISC-V processor, transitioning from Register Transfer Level (RTL) design to final GDSII using Synopsys Fusion Compiler over 32nm technology node. The processor architecture is based on the RV32I base instruction set and incorporates a 5-stage pipeline to achieve a balanced trade-off between performance and design complexity. The design methodology involved RTL synthesis, gate-level netlist generation, and successive physical design stages …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 3, 2025 · pp. 1–10 Read article
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The Impact of AI-Driven Real-Time Feedback Systems on Students’ Self-Regulated Learning and Academic Persistence in Secondary Schools, Nigeria
Abstract: Self-regulated learning (SRL) is essential for secondary school students to achieve academic success and lifelong learning competencies, particularly in contexts requiring greater learner autonomy. This expository article examines the potential of Artificial Intelligence (AI)-driven real-time feedback systems to support SRL processes—planning (forethought), monitoring (performance/control), and reflection—within Nigerian secondary education. Grounded in Zimmerman’s cyclical SRL model and Bandura’s Social Cognitive Theory, the paper conceptualises AI tools (e.g., intelligent tutoring systems, learning …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 2, 2026 Read article
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Recent Advances in Smart Polymer Composites for Plant Health Monitoring: A Strategic Integration of Sensing Mechanisms and Computational Intelligence
Abstract: Plant health assessment is crucial for agricultural production and food security, as plant diseases significantly affect crop yields and quality. This paper reviews the applications of polymers and composite materials in the evaluation of plant health, focusing on both natural and artificial polymers, carbon materials, and polymeric–nanoparticle composite materials. Various types of sensing principles, such as colorimetry, fluorimetry, surface plasmon resonance (SPR), surface enhanced Raman scattering (SERS), and interferometry, are …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 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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Gene Expression Profiling in Autism Spectrum Disorder: A Microarray Analysis Using Gse42133
Abstract: Autism Spectrum Disorder (ASD) is a diverse neurodevelopmental disorder characterized by difficulties in social interaction, communication impairments, and restricted or repetitive patterns of behavior. Despite its increasing prevalence, the underlying molecular mechanisms remain poorly understood. Advances in transcriptomics offer opportunities to investigate the gene expression changes that may contribute to ASD pathophysiology. In this study, the microarray dataset GSE42133 was analyzed, which comprises gene expression profiles from peripheral blood samples …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 37–48 Read article
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Physics-Informed Generative and Tensor-Based Framework for DNA Sequence Simulation and Genomic Structure Discovery
Abstract: In this paper, we explore the intersection of artificial intelligence (AI) and mathematical physics to propose advanced methods for DNA sequence generation and analysis. Specifically, we investigate how physics-informed Generative Adversarial Networks (GANs) and tensor network representations can be harnessed to restructure DNA for applications in genetic science. The proposed methodology offers a unique integration of concepts of thermodynamic modeling with innovative GAN architecture in order to allow the creation …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Blockchain Infused Decentralized Land Registry System
Abstract: Accurate land measurement and documentation of land ownership and use are critical for effective land administration and management. However, traditional land measurement systems are often inefficient, inaccurate, and lack transparency, which can lead to disputes, fraud, and corruption. To address these issues, we propose a smart contract-based land measurement system that provides a secure, transparent, and efficient way to measure and document land ownership. Our system utilizes smart contracts, which …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 11–19 Read article