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1984 articles for “generations” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article
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Reimagining Plastic Waste: The Impact of Eco-Bricking on Student Engagement and Community Sustainability
Abstract: Plastic pollution poses a severe threat to the environment, impacting ecosystems, wildlife, and human health. With millions of tons of plastic waste generated globally each year, innovative solutions for waste management are essential. This paper explores the eco-bricking initiative at Sovanagar High School, which transforms plastic waste into eco-bricks—sustainable building materials used for constructing green walls, benches, and other structures on the school campus. By effectively reducing plastic waste, this …
Published in International Journal of Atmosphere · Vol. 1, Issue 1, 2024 · pp. 23–25 Read article
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Review And Analysis of Application of Conductive Polymer Composites in Power-Efficient RF Circuits For 5G PAPR Reduction
Abstract: The need for low power RF circuits has gained more importance in the background of fifth-generation (5G) wireless communication systems, since the inherent PAPR characteristic of 5G signals—especially when using orthogonal frequency division multiplexing (OFDM) based techniques—becomes high. This high PAPR limits the efficiency of RF power amplifiers, increases power consumption, and induces thermal management challenges. In this context, conductive polymer composites (CPCs), based on advanced polymer matrices integrated with …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 111–125 Read article
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Recycling of Plastic Waste Using Mini Shredder
Abstract: In the current situation, plastic use is expanding daily, leading to a significant environmental problem. Plastics can negatively affect soil organisms in a variety of ways through complex interactions. For example, it has been found that microplastics seep into the soil and change its physical makeup, which lowers the soil's ability to hold water. Particularly in India, people generate 26,000 tons of plastic waste every day which is equivalent to …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 426–435 Read article
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Enhancing Terahertz Patch Antennas: The Role and Impact of Graphene
Abstract: Terahertz (THz) communication systems are gaining increasing attention because of their ability for high-speed wireless data transmission, making them suitable for the 6th-generation wireless applications. Patch antennas, commonly used in these systems, play a crucial role in signal transmission and reception. There are various types of conductive materials available for patch antennas, but the unique characteristics of graphene make it a suitable choice. This study explores the significance and contribution …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 2, 2025 · pp. 41–51 Read article
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Real-Time Analysis of E-Waste Monitoring Using Data Visualization in Power BI
Abstract: The exponential growth of electronic waste (e-waste) in India poses significant environmental and public health challenges, necessitating robust monitoring, management, and disposal strategies. This project, Real-time analysis of e-waste generated across different countries in the world and also survey report of India, seeks to provide a comprehensive assessment of e-waste production patterns, utilizing real-time data to capture dynamic shifts in waste generation and collection. By leveraging Power BI for advanced …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 1–7 Read article
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Dielectric Elastomers in Actuation and Energy Applications: Material Behavior and Design Strategies
Abstract: Dielectric elastomers (DEs), a class of electroactive polymers, have attracted significant attention for their ability to undergo large, reversible deformations under electric stimulation. This unique capability makes them highly suitable for a range of actuation and energy harvesting applications, especially in the emerging fields of soft robotics, flexible electronics, artificial muscles, and sustainable power generation systems. DEs offer compelling advantages such as low weight, mechanical flexibility, high energy density, and …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 13–18 Read article
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Selective Recovery of Valuable Chemicals from Tire Pyrolysis Oil: A Sustainable Approach
Abstract: The generation of waste/scrap/end-of-life tires (ELTs) poses severe environmental challenges globally. For the disposal of huge numbers of ELTs (generated every year) using conventional recycling methods, like as landfill or incineration, are not preferred due to their adverse environmental impacts. To overcome this problem, an alternative and promising technology is developed -the pyrolysis of waste tires. Pyrolysis is a thermochemical process that decomposes organic materials (Rubber Hydrocarbons) in the absence …
Published in Journal of Catalyst & Catalysis · Vol. 12, Issue 3, 2025 · pp. 31–43 Read article
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Photochemical Materials for Light-responsive Optical Switching: AI-optimized Design of Dynamic Visual Effects
Abstract: This paper presents an in-depth investigation into the design and behavior of photochemical materials that generate optical illusions and dynamic visual effects through light-induced molecular transformations. The study focuses on advanced photoresponsive compounds such as azobenzene and spiropyran derivatives, emphasizing their reversible optical transitions governed by photoisomerization, phase transitions, and photochromism in solid-state and polymeric matrices. Spectroscopic and kinetic analyses are employed to evaluate the influence of light wavelength, material …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 13–27 Read article
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Electromagnetic Propulsion Train for Future Transportation
Abstract: The Electromagnetic Propulsion Train project focuses on the development and analysis of a prototype system that achieves linear motion through the application of controlled electromagnetic forces. Unlike conventional railway systems that rely primarily on mechanical drive mechanisms such as wheels, axles, and traction motors, this project explores an alternative propulsion approach based on electromagnetic interaction. In this system, a sequence of electromagnets is strategically positioned along the track to generate …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 2, 2025 · pp. 25–31 Read article
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AI Voice Detection Tool
Abstract: In today’s digital era, distinguishing between AI-generated and human voices is more important than ever. This project introduces an AI-based voice detection system designed to accurately identify synthetic voices, ensuring security and authenticity across various applications like cybersecurity, media verification, and fraud prevention.Our system works by analyzing incoming audio samples and comparing them against a diverse database of both AI-generated and real human voices. Using advanced machine learning and signal …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 1–8 Read article
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Challenges, Risks, and Limitations of Vibe Coding in AI-Assisted Software Development
Abstract: Vibe coding is a new way of programming driven by LLMs (large language models). It helps developers write code from natural language. Developers can use prompts with artificial intelligence (AI) for code generation. AI assistants generate software directly through text. They can now perform tasks and understand user requirements. This process makes software development faster and easier for developers, but vibe coding has some drawbacks. Sometimes, it leads to security …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 · pp. 43–48 Read article
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Future-Ready Communication Systems: Exploring High-Speed, Adaptive, and Secure Network Solutions
Abstract: The domain of electronics communication systems has experienced rapid transformation due to the growing demand for high-speed, reliable, and intelligent communication networks. This paper presents a comprehensive analysis of emerging trends such as Fifth Generation (5G) communication systems, Internet of Things (IoT), Artificial Intelligence (AI)-enabled networks, Software-Defined Networking (SDN), optical communication advancements, and cybersecurity mechanisms. The combination of cloud computing, edge computing, and network virtualization which improve system flexibility, allow …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 1, 2026 · pp. 32–38 Read article
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The Renaissance and Resilience of CB1 Reverse Agonists: From Central Liabilities to Peripheral Promise
Abstract: Building upon these foundational insights, current research has increasingly focused on refining the pharmacological profile of CB1 reverse agonists to maximize therapeutic benefit while minimizing central adverse effects. The adverse neuropsychiatric outcomes associated with first-generation agents such as Rimonabant including anxiety, depression, and suicidal ideation highlighted the critical role of central CB1 receptors in mood regulation. Consequently, drug development strategies have shifted toward peripherally restricted CB1 reverse agonists that exhibit …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 30–35 Read article
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Machine Learning in Nuclear Medical Applications: A Review of Research Frontiers
Abstract: Nuclear medicine, encompassing PET, SPECT, and targeted radionuclide therapy, generates high-dimensional, quantitative data uniquely suited for machine learning (ML) analysis. This review synthesizes current research applications of ML across six key domains. Positron emission tomography (PET), single-photon emission computed tomography (SPECT), and targeted radionuclide therapy are examples of nuclear medicine modalities that generate high- dimensional, quantitative datasets that are particularly well-suited for machine learning (ML)-driven analysis. These imaging methods provide …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 19–24 Read article
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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 26–33 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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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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Self-Powered Piezoelectric Nano-Polymer Networks with Embedded Wireless Nodes for Distributed IoT Sensor Platforms
Abstract: Self-powered sensing systems are emerging as a promising solution for next-generation distributed Internet of Things (IoT) platforms, where lightweight, flexible, and low-maintenance devices are required for continuous monitoring. In this work, a self-powered piezoelectric nano-polymer network based on poly-vinylidene fluoride (PVDF) reinforced with BaTiO₃ nanoparticles and multiwalled carbon nanotubes (MWCNTs) was developed for flexible wireless sensing applications. The composite was designed to combine mechanical flexibility, enhanced piezoelectric response, and real-time …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Modelling and Simulation of a Combined System Geothermal Binary Plant and Parabolic Solar Concentrator
Abstract: The present work describes a new prototype that uses the concentrated solar radiation to improve the performance of geothermal power plants. Current methods of heat recovering have been used to reduce the amount of fossil fuel used to produce vapor or to increase gas pressure and temperature, depending on the type of system; however, concentrated solar energy is an unknown resource that may help to increase vapor production at a …
Published in Journal of Thermal Engineering and Applications · Vol. 8, Issue 1, 2021 · pp. 23–46 Read article