With artificial intelligence propelling rapid technological advances, many tools and frameworks have surfaced to assist virtual learning settings. They all make unique claims about how best to facilitate distance educ...
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Potatoes are one of the world's most popular and economically important crops. For many uses in agriculture, breeding, and trading, accurate recognition of potato breeds is important. In recent years, deep learnin...
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Most of the traditional cloud-based applications are insecure and difficult to compute the data integrity with variable hash size on heterogeneous supply chain datasets. Also, cloud storage systems are independent of ...
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This study aims to explore the flexural behavior of crushed clay brick (CCB) lightweight concrete (LWC) beams strengthened with rubberized strain-hardening cementitious composite reinforced with glass fiber textile me...
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Traffic rerouting is a technique used to optimize traffic flow and reduce congestion by redirecting vehicles to alternate routes. The work done in this research focuses on a specific case scenario covering a 25 k...
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Retrofitting projects play a critical role in enhancing the sustainability of existing structures, yet balancing time, cost, and environmental impact remains a significant challenge for decision-makers. This study int...
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Cloud computing has become increasingly popular due to its capacity to perform computations without relying on physical infrastructure,thereby revolutionizing computer ***,the rising energy consumption in cloud center...
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Cloud computing has become increasingly popular due to its capacity to perform computations without relying on physical infrastructure,thereby revolutionizing computer ***,the rising energy consumption in cloud centers poses a significant challenge,especially with the escalating energy *** paper tackles this issue by introducing efficient solutions for data placement and node management,with a clear emphasis on the crucial role of the Internet of Things(IoT)throughout the research *** IoT assumes a pivotal role in this study by actively collecting real-time data from various sensors strategically positioned in and around data *** sensors continuously monitor vital parameters such as energy usage and temperature,thereby providing a comprehensive dataset for *** data generated by the IoT is seamlessly integrated into the Hybrid TCN-GRU-NBeat(NGT)model,enabling a dynamic and accurate representation of the current state of the data center *** the incorporation of the Seagull Optimization Algorithm(SOA),the NGT model optimizes storage migration strategies based on the latest information provided by IoT *** model is trained using 80%of the available dataset and subsequently tested on the remaining 20%.The results demonstrate the effectiveness of the proposed approach,with a Mean Squared Error(MSE)of 5.33%and a Mean Absolute Error(MAE)of 2.83%,accurately estimating power prices and leading to an average reduction of 23.88%in power ***,the integration of IoT data significantly enhances the accuracy of the NGT model,outperforming benchmark algorithms such as DenseNet,Support Vector Machine(SVM),Decision Trees,and *** NGT model achieves an impressive accuracy rate of 97.9%,surpassing the rates of 87%,83%,80%,and 79%,respectively,for the benchmark *** findings underscore the effectiveness of the proposed method in optimizing energy efficiency and enhancing the predictive
The recent 2023 Turkey–Syria earthquakes have highlighted that liquefaction-induced settlements can lead to significant damage to overlying infrastructure. During the post-shaking stages, the excess pore water pressu...
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The lack of symptoms in the early stages of liver disease may cause wrong diagnosis of the disease by many doctors and endanger the health of patients. Therefore, earlier and more accurate diagnosis of liver problems ...
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Mobile devices within Fifth Generation(5G)networks,typically equipped with Android systems,serve as a bridge to connect digital gadgets such as global positioning system,mobile devices,and wireless routers,which are v...
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Mobile devices within Fifth Generation(5G)networks,typically equipped with Android systems,serve as a bridge to connect digital gadgets such as global positioning system,mobile devices,and wireless routers,which are vital in facilitating end-user communication ***,the security of Android systems has been challenged by the sensitive data involved,leading to vulnerabilities in mobile devices used in 5G *** vulnerabilities expose mobile devices to cyber-attacks,primarily resulting from security ***-permission apps in Android can exploit these channels to access sensitive information,including user identities,login credentials,and geolocation *** such attack leverages"zero-permission"sensors like accelerometers and gyroscopes,enabling attackers to gather information about the smartphone's *** underscores the importance of fortifying mobile devices against potential future *** research focuses on a new recurrent neural network prediction model,which has proved highly effective for detecting side-channel attacks in mobile devices in 5G *** conducted state-of-the-art comparative studies to validate our experimental *** results demonstrate that even a small amount of training data can accurately recognize 37.5％of previously unseen user-typed ***,our tap detection mechanism achieves a 92％accuracy rate,a crucial factor for text *** findings have significant practical implications,as they reinforce mobile device security in 5G networks,enhancing user privacy,and data protection.
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