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47 articles for “hidden”
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 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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Everlasting Life Achieved Through Technology in AI
Abstract: The concept of immortality Life is a philosophical idea that states life is limitless and does not stop with death, it exists infinitely. In our Sanskrit scriptures and Santana dharma teach us that there is a life of beginning and an end, which are referred to as birth and death but our souls do not perish, instead, they switch bodies. In this scenario, our memories have evaporated to protect our …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 Read article
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Sanskruti AI : Rediscovering Indian Culture Using Artificial Intelligence
Abstract: Away from old ways, many young people in India now find customs hard to reach, losing touch with sacred texts, local traditions, and deeper beliefs. Into this space steps Sanskruti AI - an intelligent tool using sound, text, and vision to bring culture closer, tailored to how today & users think and feel. Instead of flat translations, it unpacks verses from Sanskrit with layers: word-for-word sense, background context, inner meaning. …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 16, Issue 2, 2026 Read article
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Thermal Steganography: A New Way to Steal Data from Air-Gapped Computers Using Heat and Fan Noise
Abstract: Nowadays, high-security computers are "air-gapped," meaning they are not connected to the internet to prevent hacking. Cybercriminals are increasingly using direct, physical methods to access and take data instead of relying on internet-based attacks. This paper introduces a new cybersecurity threat called Thermal-Secret. Most existing heat-based attacks are very slow and fail if the room temperature changes. To solve this, we developed a Slope-Based method. Instead of looking at how …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article