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4 articles for “downstream algorithms.”
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Real-time Malicious URL Detection Using Machine Learning
Abstract: In malicious URLs (universal resource locators)discovery, antiquated classifiers are tested because of the information volume is enormous, designs are dynamical over the long haul, and furthermore the relationships among choices are modern. Feature engineering plays a crucial role in addressing these issues. To raised representation, the underlying the drawback and improve the performances of classifiers in characteristic malicious URLs.This paper proposes a mixture of linear and non-linear house transformation strategies. …
Published in Journal of Web Engineering & Technology · Vol. 8, Issue 1, 2021 · pp. 8–13 Read article
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Use of Precipitation Data from Advanced Microwave Scanning Radiometer 2 in the Forecasting of Floods in Assam
Abstract: Flood occurs most commonly from heavy rainfall but it can also result from storm surge associated with a tropical cyclone, a tsunami or a high tide coinciding with higher than normal river levels. Rainfall in the upstream of a river can also cause inundation in the downstream side of a river. Reliable and timely information is essential for appropriate flood management system. This paper explains the use of precipitation data …
Published in Journal of Remote Sensing & GIS · Vol. 6, Issue 1, 2015 · pp. 43–52 Read article
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Deployment of Fi-Wi Networks Using Teaching Learning Based Optimization Algorithm
Abstract: AbstractThe demand of bandwidth and mobility to end users is ever increasing. For fulfilling this, fiber-wireless (Fi-Wi) networks are designed by integrating the advantages of optical and wireless networks. Optical networks offer high bandwidth and stability while wireless networks offer cost efficiency and mobility. With these advantages, Fi-Wi networks also offer some challenging issues. There are four key issues in Fi-Wi networks, that are ONU placement, routing, energy saving and …
Published in Journal of Communication Engineering & Systems · Vol. 7, Issue 2, 2017 · pp. 14–26 Read article
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Intelligent Traffic Monitoring: YOLO v8 and CSV Data Integration
Abstract: The “Intelligent Traffic Monitoring: YOLO v8 and CSV Data Integration” project is a cutting-edge solution for intelligent traffic monitoring, with YOLO v8 (You Only Look Once) serving as the fundamental technology for real-time vehicle detection and traffic counting on roads. In addition to these features, the system interfaces effortlessly with data pipelines and machine learning projects by storing gathered traffic data in CSV (Comma-Separated Values) format. The major goal of …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 20–24 Read article