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810 articles for “Real-time Data”
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Seismic Hazard Evaluation through Attenuation Law Derivation and Response Spectrum Design: Bangladesh Case Study
Abstract: Bangladesh, positioned at the confluence of the Indian, Eurasian, and Burma tectonic plates, faces significant seismic hazards due to its complex geological setting. This research focuses on formulating empirical attenuation relationships and Creating a design response spectrum for assessing seismic risks in Bangladesh, using data from ten large earthquakes with magnitudes ranging from 6. 7 to 7. 9. The study creates Ground Motion Prediction Equations (GMPEs) for various structural periods …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 3, 2025 · pp. 54–63 Read article
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Advancements in Phishing Detection: Automated Systems in Real-World Scenarios
Abstract: The goal of the abstract is to offer an automated method that uses login URLs to identify real-world scenarios. Phishing is a type of cyberattack that involves social engineering, when malefactors trick victims into providing their login credentials via a login form that sends the information to a hostile site. In this research, we offer a system that uses URL analysis to detect phishing websites by comparing machine learning and …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 2, 2024 · pp. 12–17 Read article
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Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 Read article
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Transformative Impact of Artificial Intelligence on Telecommunications: Network Optimization, Predictive Maintenance, and Personalized User Experience
Abstract: This paper explores the transformative impact of Artificial Intelligence (AI) in telecommunications, focusing on network performance optimization, predictive maintenance, personalized user experiences, and ethical and regulatory challenges. AI technologies enhance communication networks by optimizing resource allocation, reducing latency, and increasing throughput through real-time adjustments and predictive analytics. Predictive maintenance, enabled by AI, helps prevent failures, reduce downtime, and lower maintenance costs by anticipating issues. The study also delves into AI's …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 1, 2025 · pp. 27–36 Read article
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Improving Healthcare Outcomes with RF-enabled Health Information Systems
Abstract: Health Information Technology (HIT) plays a crucial role in improving healthcare by making medical data more accessible, accurate, and efficient. Using radio frequency (RF) technology, HIT enables the wireless sharing of important health information—like patient records, and treatments—between patients, doctors, and other healthcare providers. This helps reduce paperwork, cut costs, and improve the quality of care. By reducing the reliance on paper-based records, RF-based HIT helps streamline administrative processes, cut …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 1, 2025 · pp. 8–13 Read article
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AI Application in the Creation of Medications for COPD
Abstract: The crippling lung condition known as chronic obstructive pulmonary disease (COPD) is typified by a continuous restriction of airflow, which results in increased respiratory dysfunction and a reduced quality of life. The rising incidence of COPD worldwide emphasizes the pressing need for innovative pharmaceutical approaches to address the illness. Even though COPD care has advanced significantly, most current medications concentrate on symptom relief rather than disease change. This gap in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 01–05 Read article
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Versatile CNC Machine for Tabletop Use Enhanced with Machine Learning Integration
Abstract: In the realm of tabletop multipurpose CNC machines, the integration of machine learning represents a groundbreaking advancement potentially revolutionary in the field of desktop manufacturing. This research explores the seamless incorporation of machine learning algorithms into tabletop CNC machines to enhance their capabilities, performance, and user experience. Through case studies and examples, we demonstrate the profound impact of machine learning integration in key areas of CNC machining, such as accurate …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 353–361 Read article
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Flying Drone Using KK Flight Controller
Abstract: This paper presents the design, development, and testing of a quadcopter drone using the KK2.1.5 flight controller, with an emphasis on stability and educational value. The KK2.1.5 controller features are inbuilt LCD screen, inbuilt programming, enabling direct configuration and tuning without the need for a computer interface, which makes it highly suitable for beginners and students. The drone is built using a modular frame architecture, which allows for easy replacement …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 20–25 Read article
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Cybersecurity in Web Automation: A Machine Learning Approach to Lightweight Intrusion Detection
Abstract: Launch-Attack is a lightweight and practical threat-detection framework designed specifically for smaller web-automation environments, including setups that rely on tools such as Selenium. Rather than aiming to replace large enterprise-grade security platforms, the framework focuses on offering an accessible option for developers, testers, and researchers who need real-time monitoring without the heavy resource demands of traditional systems. The model relies on machine-learning techniques implemented through Scikit-learn, enabling it to detect …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 34–40 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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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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Quantum Mechanics: Revolutionizing Pharmaceutical Sciences
Abstract: Quantum physics and pharmacy have generally been regarded as distinct areas—one investigates the microlevel behavior of non-living matter while the other concentrates on intricate biological systems. Nevertheless, progress in life sciences has increasingly depended on molecular-level insights, whereas quantum physics has advanced beyond basic principles to impact real-world uses. This intersection provides new opportunities for, pharmacy. Quantum entanglement, which allows for instantaneous relationships between particles, can be utilized for secure …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 1, 2025 · pp. 72–77 Read article
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An Empirical Analysis of Bluetooth Low Energy Reliability Challenges for Offline Messaging Applications
Abstract: In today's hyper-connected world, modern communication relies heavily on centralised internet infrastructure, making robust offline messaging solutions increasingly essential. A crucial vulnerability is revealed by network failures, natural disasters, and distant region deployments: communication breaks down when internet connectivity does. Due to its low power consumption and almost ubiquitous availability in contemporary smartphones, Bluetooth Low Energy (BLE) has become a promising candidate for offline, device-to-device communications. This study presents an …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 2, 2026 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Application of Grey Wolf Optimizer (GWO) strategy for Malware Analysis
Abstract: The ever-evolving landscape of cybersecurity necessitates continuous advancements in malware analysis techniques. This study explores the deployment of the Grey Wolf Optimizer (GWO) algorithm as a novel bio-inspired optimization mechanism to address the challenges posed by modern malware threats. The primary objective is to enhance various facets of malware analysis, including feature selection, parameter optimization, and the overall efficacy of malware detection models. The study begins by introducing the GWO …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 43–53 Read article
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Fuzzy Mathematics in Decision-Making: A Quantitative Perspective
Abstract: Fuzzy mathematics plays an increasingly generalized role in decision-making, and thus, this paper details different types of fuzzy mathematics and highlights other possible alternatives alongside fuzzy methodologies. Fuzzy models offer a versatile and precise approach to assessing complex and uncertain situations using fuzzy sets, membership functions, linguistic variables, and aggregation methods. Through the lenses of time, cost, and quality, the project management case study illustrates how fuzzy logic effectively evaluates …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 6–12 Read article
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A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article
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HirePrep: A Microservice-Based Integrated Placement Preparation Platform with AI Assistance
Abstract: Preparing for campus placements can be a confusing and time-consuming process. Students have to use different platforms for things like practice tests, study materials, talking to people, and getting updates from the administration. This is not a waste of time, but it also makes it harder for students to be productive and clear about what they need to do when they are getting ready for their careers. To make things …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 25–37 Read article
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Structural Health Monitoring of Polypropylene Fiber- Reinforced Composite Using Accelerometer Sensors
Abstract: This study explores the application of accelerometer sensors for structural health monitoring (SHM) in evaluating the performance of polypropylene fiber-reinforced composites (PFRC). Incorporating polypropylene fibers into concrete enhances its structural integrity and durability. However, accurately assessing PFRC behavior under various conditions is crucial for its practical application in construction. This research employs advanced accelerometer sensor technology for real-time monitoring and assessment of PFRC performance. Experimental investigations captured and analyzed the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 621–634 Read article
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Adaptive E-Learning Algorithms and Heutagogy: A Systematic Analysis
Abstract: The proliferation of artificial intelligence (AI) and machine learning (ML) technologies has transformed the digital education landscape by enabling adaptive e-learning systems capable of personalizing content and optimizing learning paths. This study provides a systematic analysis of adaptive e-learning algorithms within the framework of heutagogy, an educational paradigm that emphasizes learner autonomy, self-direction, and capability development. The convergence of adaptive technologies with heutagogical principles offers new avenues for creating more …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 33–38 Read article