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1280 articles for “intelligent”
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Innovations in Mineral Science and Engineering for Sustainable Resource Development
Abstract: The growing global demand for mineral resources, coupled with increasing environmental and social concerns, has intensified the need for sustainable approaches in mineral science and engineering. Traditional mining and mineral processing practices, while essential for industrial development, are often associated with high energy consumption, resource depletion, and environmental degradation. In response, recent innovations in mineral science and engineering have focused on improving resource efficiency, minimizing environmental impact, and ensuring long-term …
Published in International Journal of Minerals · Vol. 3, Issue 1, 2026 · pp. 31–36 Read article
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Spintronic Logic Device Modeling and Energy Optimization for Beyond-CMOS Computing Systems
Abstract: The continuous scaling limitations of conventional CMOS technology have accelerated the exploration of alternative computing paradigms for next-generation low-power and high-performance systems. Spintronic logic devices have emerged as a promising solution due to their non-volatility, ultra-low switching energy, high integration density, and compatibility with beyond-CMOS architectures. This research presents a comprehensive modeling and energy optimization framework for spintronic logic devices applied in beyond- CMOS computing systems. The proposed work investigates …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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AWPRATOR: Autonomous Waste Picking Robot and Tracking of Routes
Abstract: Traditional waste management systems, especially in urban and semi-urban areas, relies heavily on manual methods like manual collection of waste, and fossil-fuel based garbage trucks. These methods often face many challenges such as inefficient high dependency on human labor, inefficient planning of routes, health risk for sanitation workers, lack of adaptability, real-time decision making. With the increase in the number of smart cities, the need for intelligent, autonomous, and eco-friendly …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 13–21 Read article
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Cognitive AI-Based Quality Control and Operational Optimization of Polymer Composites for Healthcare Applications
Abstract: The use of polymer composite materials in healthcare is on the rise because of their adjustable mechanical characteristics, biocompatibility and structural flexibility. Yet, it is difficult to ensure stable quality of such composites due to process-related defects, heterogeneity of the material and the lack of real-time adaptive control. The proposed study suggests the use of cognitive AI-based framework of quality control and optimization of operation of polymer composite systems which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 571–591 Read article
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Silicon Symphony: The Science of Semiconductors Circuits
Abstract: Modern electronics are built on the foundation of semiconductor circuits, which precisely and efficiently control the flow of electrical impulses. This article takes a look at the underlying physics of semiconductor materials and how their unique electrical properties allow the design and functioning of diodes, transistors and integrated circuits. This study links microscopic scientific principles to the behaviour of real circuits. It considers essential concepts such as charge carriers, doping …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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The Synthetic Media Threat: Generative AI and Deepfake Technology enabled Synthetic Media as Emerging Vectors of Cyberterrorism
Abstract: Cyberterrorism for most part of its academic and general understanding has been known and studied through conventional way such as a) malware deployment b)denial of essential services c) attacks on critical infrastructure, however with rapid changes in information technology as well as recent swift proliferation of generative artificial intelligence and deep fake technologies a completely new and unexamined dimension of threat vector has emerged, further expanding the threat areas are …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 2, 2025 Read article
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Development of Neuromorphic Polymer Composites Using IoT Sensing and Brain-Inspired Learning Algorithms
Abstract: This research aims to develop neuromorphic polymer composites by combining conductive sensing materials, IoT-based sensing data collection and brain-inspired learning models for adaptive response. Hybrid conductive polymer composites were developed by adding carbon nanofibers and graphene Nano platelets to a thermoplastic polymer. IoT sensors (strain, temperature) were employed to collect real-time sensing data that was combined with environmental data. A material-aware neuromorphic learning algorithm was created with event-driven spike coding …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 755–784 Read article
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pH-Responsive Smart Polymer Nanocomposites for Anti-Corrosive Coatings
Abstract: Metallic corrosion under adverse marine and industrial conditions imposes gigantic financial burdens and risks worldwide. Conventional waterproofing waterborne epoxy has passive barrier protection, but is also inherently microporous, lacking intrinsic repair ability against mechanical damage and thus rapidly decays. This is a critical gap that this work tries to bridge by designing a new pH-responsive hybrid polymer nanocomposite by using polyethyleneimine-tannic acid-cerium functionalized boron nitrate nanosheets with chitosan-capped mesoporous silica …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 201–213 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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Machine Learning–Guided Cognitive RF System with Dynamic FFT Resolution and Multiplier Reconfiguration for Adaptive Anti-Jamming Communication
Abstract: This paper presents a hierarchical adaptive RF communication system that integrates signal quality-based pre- processing with machine learning-driven signal classification to achieve robust and resource-efficient operation in dynamic, interference-prone environments. Unlike prior art that addresses adaptive RF, ML classification, or anti-jamming individually, this work uniquely combines real-time SNR/RSSI-based signal strength estimation with dynamic FFT size selection (64-, 256- , or 512-point) and arithmetic-level multiplier reconfiguration (CORDIC, Distributed Arithmetic, and hybrid …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Photonic-Assisted Spintronic Solid-State Switching Model for High-Speed Memory Devices
Abstract: The rapid advancement of high-speed computing and data-centric applications has intensified the demand for energy-efficient and ultra-fast memory technologies. This paper proposes a Photonic-Assisted Spintronic Solid-State Switching Model for next-generation high-speed memory devices. The proposed framework integrates photonic excitation mechanisms with spintronic switching dynamics to enhance data transfer speed, minimize switching delay, and reduce power dissipation in solid-state memory architectures. By combining optical pulse-assisted spin polarization with magnetic tunnel junction-based …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Non-Small Cell Lung Cancer: Types, Pathogenesis, Diagnosis, and Novel Therapeutic Strategies
Abstract: Non-small cell lung cancer (NSCLC) is the most prevalent type of lung cancer, accounting for over 85% of all cases globally. It remains one of the primary causes of cancer-related death due to its rapid progression, few early symptoms, and late detection. The three main forms of non-small cell lung cancer (NSCLC) are adenocarcinoma, squamous cell carcinoma, and giant cell carcinoma; each has a unique histology, prognosis, and response to …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 2, 2026 Read article
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Autonomous Calibration of Medical Devices Using Synthetic Biosignals and Adaptive Learning
Abstract: The accuracy and reliability of modern biomedical diagnostic devices are critically dependent on effective calibration mechanisms capable of handling dynamic physiological and environmental variations. Conventional calibration approaches, which rely on static reference signals and manual adjustments, are inadequate in addressing challenges such as sensor drift, noise interference, motion artifacts, and long-term performance degradation. To overcome these limitations, this research proposes an innovative AI-driven adaptive biosignal simulation and calibration architecture for …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article
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Advances in Stimuli-Responsive Smart Drug Delivery Systems: A Systematic Review
Abstract: Imagine a world where medicines work smarter, not harder. Stimuli-responsive drug delivery systems (SRDDS) are transforming healthcare by releasing therapeutic agents in response to specific triggers. These triggers can be internal, like changes in pH or temperature, or external, like light or magnetic fields. By leveraging these triggers, SRDDS can optimize treatment and minimize side effects. The potential applications of SRDDS are vast, from cancer treatment to gene delivery and …
Published in Trends in Drug Delivery · Vol. 13, Issue 2, 2026 Read article
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Recent Innovations in Semiconductor Materials for Smart Electronic Devices
Abstract: Recent advancements in semiconductor materials have significantly transformed the design, performance, and functionality of smart electronic devices such as smartphones, wearable systems, IoT devices, autonomous systems, and biomedical electronics. With the continuous demand for higher processing speed, lower power consumption, improved thermal stability, and extreme miniaturization, traditional silicon-based semiconductor technology is facing major limitations. As device dimensions shrink to the nanometer scale, challenges such as leakage current, heat dissipation, and …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 2, 2026 Read article
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Polymer Composite-Enabled UAV Platform for Edge AI-Based Precision Agriculture: A System-Level Evaluation
Abstract: This study investigates the system-level role of commercially available polymer composite materials in enabling lightweight and energy-efficient unmanned aerial vehicle (UAV) platforms integrated with edge artificial intelligence for real-time agricultural monitoring. Rather than developing or experimentally characterizing new composite materials, the work evaluates fiber-reinforced polymer (FRP) composites and epoxy-based laminates as enabling structural components whose established properties support UAV performance in precision agriculture. Their high strength-to-weight ratio, corrosion resistance, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 218–240 Read article
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Gene Edited Livestock for Enhanced Feed Efficiency and Metabolic Adaptation Through Precision Genomic Interventions
Abstract: Advances in gene editing technologies have transformed the landscape of livestock production by enabling precise manipulation of genetic material associated with productivity, health, and environmental adaptability. Tools such as CRISPR Cas9 and emerging next generation editors allow targeted modifications that improve feed efficiency, growth performance, nutrient utilization, and stress tolerance in farm animals. This review highlights the genetic basis of feed efficiency and metabolic regulation, focusing on key genes and …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 16, Issue 2, 2026 Read article
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Multi-Scale Analysis of Polymer Based Energy Storage Systems for High Performance Battery Applications
Abstract: The energy storage systems based on polymers are becoming promising materials for the next generation of high performance batteries because of their excellent mechanical flexibility, improved safety, and favorable electrochemical properties. Even with computational tools in Python, polymer-based energy storage systems remain plagued by poor ionic conductivity, complicated electrochemical reactions and potential thermal runaway. Therefore, a multi-scale model is proposed to improve battery performance, thermal stability, reliability, and large-scale deployment …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1035–1048 Read article