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404 articles for “network performance”
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Leveraging IoT for Real-Time Disaster Management: Enhancing Preparedness and Response Through Smart Monitoring
Abstract: Natural disasters, including floods, earthquakes, and wildfires, pose risks to human life, infrastructure, and the environment. Many of the technological innovations are there, but in managing such disasters, there still is room for inefficiencies resulting from communication delay, unavailability of real-time data, and poor coordination at times. The inefficiencies lead to response times that are too long, inappropriate allocation of resources, and increased vulnerability to the impacts of disasters. Integration …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 11–17 Read article
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A Knowledge Graph Approach for Breast Cancer Diagnosis and Data Sharing Platform Implementation in the Context of Human Papillomavirus Infection
Abstract: Background: Breast cancer remains among the most prevalent malignancies in women worldwide, and effective diagnosis and data integration continue to challenge clinical practice. Diagnostic reports from mammography and ultrasound contain rich clinical information that is often under-utilised due to heterogeneous formats and limited data-sharing infrastructure. In the context of human papillomavirus (HPV) infection, which may influence oncogenic pathways and data complexity, advanced computational methods offer new solutions to this problem. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Intelligent Electromagnetic Synthesis: An AI-Driven IoT Framework for Adaptive Antenna Design in Missile Navigation
Abstract: The rapid evolution of hypersonic and long-range tactical missile systems necessitates antenna architecture capable of maintaining robust communication links under extreme thermal, mechanical, and signal-jamming environments. Traditional antenna design methodologies often relying on iterative simulation cycles and static optimization are increasingly insufficient for the real-time requirements of modern aerospace navigation. This paper proposes an AI-driven, IoT- integrated framework that facilitates autonomous antenna design and performance optimization. By deploying a distributed …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Application of Game Theory Principles for Opportunistic Routing in MANETS
Abstract: This article explores the application of game theory principles to enhance opportunistic routing in mobile ad hoc networks (MANETs). MANETs are characterized by their dynamic topology, limited resources, and lack of infrastructure, making traditional routing protocols less efficient. Opportunistic routing leverages the mobility of nodes and the broadcast nature of wireless communication to achieve reliable message delivery. However, existing opportunistic routing algorithms may suffer from challenges such as high message …
Published in International Journal of Mobile Computing Technology · Vol. 2, Issue 1, 2024 · pp. 1–8 Read article
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Mechanical Strength Prediction of Nano-Silica Concrete Composites Using Machine Learning Techniques
Abstract: Nano-silica, or nanosilica, refers to silicon dioxide nanoparticles, which are a kind of silica (SiO₂) with diameters that often fall below 100 nanometers. This nanomaterial has attracted considerable attention because of its distinctive characteristics and diverse array of uses, notably in augmenting the performance of materials such as concrete. The integration of nanoparticles with cementitious matrix in nano-silica concrete offers a viable approach to improving the mechanical characteristics and longevity …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 963–973 Read article
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Mood Mate: A Solid-State Edge-AI System for Real-Time Facial Emotion Recognition
Abstract: Recent progress in solid-state electronics and embedded vision systems has enabled real-time emotion-aware applications at the edge. This paper presents MoodMate, a solid-state edge-AI framework for real-time facial emotion recognition using camera-based sensing and embedded processing. The proposed system integrates a solid-state image sensor with an AI- driven emotion classification pipeline optimized for low-latency and resource-constrained environments. Intelligent, emotion-aware apps can now be deployed right at the network edge thanks …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 24–30 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 Read article
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Exploring the Viability and Implications of Quantum Communication in 6G Networks
Abstract: The development of telecommunication systems has brought us to the era of 6G, characterized by remarkable connectivity, speed and performance achievements. This article investigates the fusion of quantum communication into the architecture of 6G networks as a new approach to achieving security and efficiency. Using quantum mechanics principles, such as superposition and entanglement, quantum communication allows bloodless encryption and secure data transmission. The theoretical frameworks and quantum networks for 6G …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 1, 2024 · pp. 01–14 Read article
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Detecting Phishing Websites Using Hybrid Methodologies
Abstract: In the digital era, personal information theft has become a widespread and increasingly severe crime. Cybercriminals, often known as hackers, use deceptive strategies, with phishing websites being a major method for stealing confidential data. These fake websites imitate legitimate ones, tricking users into revealing sensitive personal and financial information, which has led to a rise in fraud cases. To address this escalating threat, a comprehensive research paper is proposed. This …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 59–65 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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Hybrid Approach for Community Detection Using Deep Learning Techniques
Abstract: Community detection in complex networks is a fundamental problem with applications across diverse domains, ranging from social networks to biological systems and beyond. Traditional methods based on graph theory have been widely used for identifying communities within networks. However, the intricate and evolving nature of modern networks demands more sophisticated approaches. This research work proposes a hybrid approach that combines the strengths of deep learning techniques with traditional community detection …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 18–26 Read article
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Ecomotion Cityglide Commuter E-Bike
Abstract: The transition from conventional gasoline motorcycles to electric bikes represents a pivotal step in addressing the increasing demand for sustainable transportation solutions in urban environments. This paper meticulously explores the multifaceted aspects of this transition, focusing on the technological advancements, design innovations, and societal implications associated with the adoption of electric bikes. Electric bikes, powered by Brushless DC (BLDC) motors and rechargeable battery packs, offer a suite of benefits over …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 1, 2024 · pp. 43–49 Read article
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Environment- friendly Pavement Construction Using Plastic Trash and Reclaimed Asphalt Pavement-An Overview
Abstract: Plastic pollution has emerged as a significant environmental concern, with detrimental effects on ecosystems and human health. As a waste product contaminating air, water, and land, plastic poses a grave threat to the environment, perpetuating a global crisis. Its non-biodegradable nature means that once produced, plastic persists indefinitely, accumulating in landfills, water bodies, and natural habitats. This widespread accumulation of plastic waste not only compromises the aesthetic value of landscapes …
Published in Journal of Polymer & Composites · Vol. 12, Issue 3, 2024 · pp. 116–123 Read article
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Advancements in Agricultural Forecasting: A Review of Machine Learning Based Crop Yield Prediction
Abstract: Agricultural productivity plays a critical role in global food security, and accurate crop yield prediction is essential for optimizing resource allocation and decision-making in farming. The rapid advancements in Machine Learning (ML) and Deep Learning(DL)have transformed agricultural forecasting, enabling data-driven approaches for crop prediction. This review paper provides a comprehensive analysis of various ML and DL techniques applied in crop yield forecast, highlighting the ineffectiveness, challenges, and future directions. The …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 32–38 Read article
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Supply Chain Design Considering Social and Environmental Risks
Abstract: The aim of the research is to design a supply chain taking into account social and environmental risks. In this research, an attempt was made to present a model that, by considering variables close to the real world, simultaneously considers cost and sustainability issues for designing a meat supply chain network, including locating facilities, using technology in them, how products flow in the network, etc. In order to examine the …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 35–43 Read article
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E-Commerce Clothing Platform with Virtual Try-On
Abstract: The inability to physically evaluate garments remains a major limitation in online clothing commerce. Customers often depend on static product images and generalized sizing charts, which do not accurately represent individual body proportions. This frequently leads to uncertainty during purchase decisions and increased product return rates. To address this limitation, this research proposes a web-based clothing e-commerce platform integrated with an intelligent virtual try-on mechanism. The system allows users to …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 17–24 Read article
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A Comprehensive Analysis of Machine Learning Models for Credit Card Fraud Detection
Abstract: This paper presents an indepth comparison of various machine learning models—Logistic Regression, Support Vector Classification (SVC), and Neural Networks (NN)—in the context of credit card fraud detection. The analysis spans multiple performance metrics, including accuracy, F1 score, precision, recall, and computational efficiency. Logistic Regression demonstrates competitive performance in terms of accuracy, but its poor precision renders it unsuitable for fraud detection tasks. Conversely, the Neural Network exhibits balanced precision and …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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Randomized Latent Vectors for Enhanced Reinforcement Learning Exploration
Abstract: This paper investigates Random Latent Exploration (RLE), a novel reinforcement learning technique that enhances exploration using randomized latent vector conditioning. I evaluate RLE’s performance across various environments, including discrete control tasks (FourRoom), continuous control (IsaacLab), and complex visual domains (Atari games). The core approach augments traditional reward functions with intrinsic rewards, calculated as the dot product between state features and periodically resampled latent vectors. The policy and value networks are …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 19–25 Read article
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Drone Swarms: An overview and working in network control systems
Abstract: The review of multi-agent systems, including drone swarms, has gained momentum due to their ability to exhibit cooperative behavior. Automating the control of a drone swarm poses substantial challenges due to the diverse wireless, networking, and environmental constraints each drone faces. To address these challenges, we treat drone swarms as Networked Control Systems (NCS), integrating the overall system control within a wireless communication network. This approach relies on a strong …
Published in International Journal on Drones · Vol. 1, Issue 1, 2025 · pp. 13–35 Read article
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Unification and DC Conductivity of PDMS/NiNPs Nanocomposite
Abstract: The DC conductivity of nickel nanoparticles–polydimethylsiloxane (NiNPs–PDMS) composite materials has attracted considerable attention due to their promising applications in flexible electronics, sensors, and energy storage devices. The electrical performance of these composites is largely governed by the formation of conductive networks within the insulating polymer matrix. Incorporating nickel nanoparticles into PDMS introduces conductive pathways that significantly enhance DC conductivity once a critical percolation threshold is reached.Several key factors influence the …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 1, 2026 Read article