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532 articles for “network-based”
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Optimized Sentiment Analysis Through TextBlob and Hybrid RNN Models
Abstract: In today’s world, analyzing people’s feelings from what they write online has become very important. This is because there is a large amount of content created by users. To make this analysis accurate and fast, we present a method. This method uses a mix of two approaches: one that looks up words in a dictionary and another that uses computer learning. TextBlob is an affordable tool for getting an initial …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 29–28 Read article
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Overview AI-Driven Antenna Technologies and Privacy- Preserving Methods for Next-Generation 6G Wireless Systems
Abstract: The next generation of wireless communications, 6G, will be built on the convergence of artificial intelligence (AI) and advanced antenna systems. AI-driven antennas are poised to address the unprecedented requirements for data rate, reliability, adaptability, and ubiquity in future networks. An overview of current advancements in AI-enabled antenna systems for 6G networks is provided in this study. From traditional base station deployments to distributed, cell-free, and user-centric frameworks, it examines …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 28–34 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
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AI-Driven Lightning Strike Prediction Using Polymer-Integrated Sensor Platforms for Climate-Resilient Energy Systems in India
Abstract: Lightning strikes are a major climate-related threat to India, resulting in severe human injuries as well as regular damages to the power transmission network and renewable energy infrastructure. This research aims to introduce the concept of an AI-based lightning strike prediction and mitigation system with the integration of polymers for making climate-resilient energy infrastructure. Multidata are collected based on satellite images, climate variables, as well as surface-based sensing modules, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 234–242 Read article
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Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Method: A Comprehensive Review
Abstract: Structural health monitoring (SHM) has a critical role in ensuring civil infrastructure safety, reliability, and durability through real-time, condition-based monitoring. Traditional SHM systems employ hundreds of sensors such as accelerometers, strain gauges, and displacement transducers for monitoring vast amounts of data for structural inspection, but do not effectively manage complicated nonlinear data. This research paper, “Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Methods,” investigates …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
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Multi-factor Fused Lightpath QoT Prediction for Optical Networks: A Multiple Reservoir Analysis Strategy
Abstract: Investigating the channel quality of transmission (QoT) in-depth is crucial for responsive and instant transparent optical network management. However, current lightpath QoT predictions are devoted to univariate modeling. Due to the QoT metrics complicated time-varying process and the existing effects of inter-channel factors, despite the use of an advanced and efficient echo state network (ESN), it is difficult to obtain ideal results in univariate prediction mode. Thus, this paper considers …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 1, 2024 · pp. 28–34 Read article
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Pneumonia Detection and Classification Using Deep Learning
Abstract: Pneumonia, an infectious lung disease primarily caused by bacteria, often exacerbated by environmental factors, leads to the accumulation of pus in the lung’s alveoli. Accurate diagnosis through chest X-rays, ultrasounds, or lung biopsies is crucial to avoid misdiagnosis and ensure proper treatment, crucial for patients’ quality of life. Diagnostic capacities have been greatly improved by deep learning advances, especially with convolutional neural networks (CNNs). This research presents a robust CNN-based …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 9–19 Read article
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IoT-Enabled Authentic Ration and Material Distribution Systems
Abstract: A home Ration Certificate is an essential item. The largest retailer system in India is Public Distribution System (PDS). A ration card is provided by the public distribution network, which is run by the state administration. All people have ration cards for purchasing essential consumers material like wheat, rice, kerosene, and oil. The present ration distribution system has many problems such as authentication problems, waste of time in queues, lots …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 26–34 Read article
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Using the R Software to Conduct Network Meta-Analysis on Diabetes Data” h
Abstract: A meta-analysis's goal is typically to quantify the total treatment effect and draw conclusions regarding the differences in effects between the two treatments. Meta-analysis is a quantitative method for combining the findings of several studies in the social and medical sciences.. A meta-analysis might be of three typical forms. Network-wide, pairwise, and multivariate meta-analyses are all possible. The integrated assessment of more than two treatments is generally made possible by …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 2, 2024 · pp. 57–76 Read article
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Facial Emotion Detection and Its Applications
Abstract: Facial emotion detection (FED) is an interdisciplinary field that integrates artificial intelligence, computer vision, and machine learning to recognize and interpret human emotions based on facial expressions. The development of FED systems has been propelled by advancements in deep learning, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which enhance recognition accuracy. Feature extraction techniques, including geometric and appearance-based methods, play a crucial role in classifying emotional states. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 8–12 Read article
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Multi-Layered AI-Driven Paradigm Shift in IoT Ecosystem Security
Abstract: As the Internet of Things (IoT) continues to weave itself into the fabric of modern life – from smart homes and industrial automation to healthcare and urban infrastructure – the associated security vulnerabilities have become increasingly apparent. Traditional security mechanisms, often built on static rules and perimeter-based defenses, struggle to keep pace with the scale, heterogeneity, and dynamic nature of IoT ecosystems. In response, artificial intelligence (AI) has emerged as …
Published in Journal of Communication Engineering & Systems · Vol. 16, Issue 1, 2026 · pp. 13–21 Read article
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Reinforcement Learning for Adaptive Sensing with Shape Memory Polymer-Based IoT Nodes
Abstract: The rapid expansion of intelligent sensing in the Internet of Things (IoT) has revealed the pressing need for materials and algorithms capable of self-adaptation in volatile environments. Conventional polymer-based sensors and static control strategies often fail to capture nonlinear thermo-mechanical dynamics, leaving them unsuitable for unpredictable operating conditions. Although prior studies have improved polymer composites or introduced algorithmic optimization independently, few attempts have coupled the adaptability of smart materials with …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 370–391 Read article
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Li-Fi based Underwater Audio and Data Transmission System
Abstract: Visible Light Communication, or Li-Fi (Light Fidelity), is a wireless optical networking technique used for communication (VLC). Due to its lack of RF communication's drawbacks, such as water absorption and scattering, Li-Fi has the potential to completely transform underwater communication. This project suggests utilizing two Arduinos, a solar panel, a speaker, a display, an amplifier, a laser, a battery, and other components to create a Li-Fi based underwater audio and …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 2, 2024 · pp. 23–29 Read article
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Spatiotemporal Analysis of Mean-Field Coupled Lorenz Oscillators for Applications in Electronic Network Design and Chaotic Synchronization
Abstract: This study investigates the spatiotemporal behavior of a network of 100 coupled Lorenz oscillators interacting through mean-field coupling with coupling strength κ = 0.1 and explores its relevance to electronic system design and nonlinear network architectures. While each oscillator follows classical Lorenz dynamics, the coupling mechanism enables collective behavior that resembles synchronization phenomena observed in distributed electronic and communication systems. Numerical simulations reveal rich dynamical characteristics including partial synchronization, emergent …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 Read article
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Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach
Abstract: Alzheimer’s disease (AD) is a neurological condition that worsens with time and impairs a patient’s quality of life by causing cognitive loss. For prompt intervention and management of AD, early identification is essential. In this work, we propose a deep learning-based method for automatically classifying Alzheimer’s disease from medical imaging data using convolutional neural networks (CNNs). Our algorithm is intended to evaluate brain MRI images and detect anatomical variations suggestive …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 Read article
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Exploring Practical Applications of Artificial Neural Networks: A Review
Abstract: Computational models called artificial neural networks (ANNs) are modeled after the structure of the human brain. These models are designed to process information and learn from data. Artificial neural networks, or ANNs, are composed of interconnected artificial neurons layered to resemble the brain's neural network.. Through training, ANNs adjust the connections between neurons based on labeled data, enabling them to recognize patterns and perform specific tasks. Despite their efficacy in …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 2, 2024 · pp. 1–11 Read article
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Design and Development of an Electromagnetic Propulsion Train
Abstract: The recent advancement of new transportation techniques led to the search for methods of propulsion that were superior to classical mechanical systems. Among these new moments, electromagnetic propulsion (EMP) has attracted attention because this technique allows for motion generation via electromagnetic force without using conventional wheel-based friction processing. The paper describes the conceptual design, principle of working and performance evaluation of a prototype model train to be propelled electromagnetically.The system, …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 19–24 Read article
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Polymers and others Advance Materials: A State-of-the-Art Review
Abstract: Developing emerging technologies requires pushing the boundaries of material science. Right now, conventional neat polymers simply do not last long enough in the field. They suffer from sudden mechanical failure, struggle with thermal instability, and throwaway disposal methods have created a massive environmental crisis. To tackle these exact issues, this review provides a critical evaluation of two rapidly growing solutions: sustainable bio-composites and self-healing polymer systems. Rather than offering a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 108–119 Read article
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Advancing IoT Security through Blockchain-based Approaches
Abstract: The emergence of blockchain technology has revolutionized various industries, including the Internet of Things (IoT), by providing a decentralized and secure platform for data management and transaction processing. However, securing IoT devices and networks remains a significant challenge due to inherent vulnerabilities and the increasing sophistication of cyberattacks. Blockchain-based security approaches have shown promise in addressing these challenges, yet their adoption is hindered by a lack of comprehensive taxonomy and …
Published in Trends in Electrical Engineering · Vol. 15, Issue 1, 2025 · pp. 1–34 Read article
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Face Detection and Recognition Using MTCNN and FaceNet
Abstract: Face detection and face recognition are major tasks in the field of computer vision with several real-world applications and many products being developed in the same field. This study gives a detailed implementation of the product that is developed for accurate detection and recognition of faces along with audio output of the face detected. This development would act as a base for a few future products that can be developed …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 132–140 Read article