This paper aims to explore various classification models and data processing techniques for classifying defects on steel plates. The study is based on a dataset of steel plates with seven different types of defects an...
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The industrial sector grapples with a critical challenge in mitigating the impact of leaks, posing threats to environmental sustainability and operational resilience. Existing technologies, including machinelearning ...
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American Sign Language is a non-verbal communication language that uses the motion of the hand and changes in hand shape to convey its meaning. It is the main mode of communication for those with hearing and language ...
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Wearable devices that automatically detect and predict seizures could be life-changing technology for patients suffering from epileptic seizures. These devices can help in constant monitoring and detection of seizures...
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Smart advertising is growing in popularity and affecting businesses. Smart advertising is a more friendly, interactive, personalised, and creative method of promoting a product, and attempts to delight clients. AROUND...
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ISBN:
(纸本)9798350333398
Smart advertising is growing in popularity and affecting businesses. Smart advertising is a more friendly, interactive, personalised, and creative method of promoting a product, and attempts to delight clients. AROUND is a social networking service that emphasizes smart advertising through an effective recommender system. The system considers user profiles, history, social network connections, mood, and IoT-supported positioning to select the most relevant ads using machinelearning technology. Although the current deployment of the AROUND system is based on the cloud, an edge-based architecture provides relevant improvement in terms of system response time. In this paper we extend the edge-based strategy to leverage the potential of federated learning on multiple distributed edge servers. We show that federated learning can take advantage of the distributed nature of the system, and leverage the specificities of local features. In fact, in this research, we propose a novel federated learning solution to provide smart advertising as a classification problem which uses ensemble methods and logistic regression as internal (local) models and meta-heuristic algorithms for federated learning aggregation. As part of the experiments, we prove this technology on a real data set with more than one million registers, and show the efficiency in terms of enhanced accuracy and improved training and response speed.
With rising industrialization, India confronts increasing difficulties in maintaining air quality regulations. This research proposes a comprehensive analysis and prediction framework based on machinelearning approac...
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Online learning is different from offline learning in the classroom with supervision from the lecturer. Online learning using the learning Management System (LMS) media requires high awareness from students because th...
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The recent advancement of pretrained models shows great potential as well as challenges for privacy-preserving distributed machinelearning technique called Federated learning (FL). With the growing demands of foundat...
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When a student chose a college, there are various factors that come into the picture. Students generally look for the outcome and, in this case, it is being placed. Every institution strives to have a strong Placement...
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Cervical cancer, accounting for 7.9% of cancers in women globally, is a critical health challenge, particularly due to its asymptomatic nature in early stages. This study proposes a machinelearning-driven framework t...
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