Uterine cancer is a serious worry for women all over the world, and we have used multi-omics datasets to present a model that predicts the survival rate of uterine cancer patients by combining machine learning approac...
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This study presents a machine learning approach for Diabetic Retinopathy (DR) classification, integrating advanced preprocessing, feature extraction, and adaptive sampling. Preprocessing techniques, including CLAHE, g...
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The COVID-19 pandemic has ravaged public health in a manner that is unprecedented: millions of infections and fatalities worldwide. Now that the immediate crisis seems to recede, there is growing concern over long-ter...
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In the dynamic era of online education, the pursuit of a personalized and effective learning experience is paramount. A transformative approach in online education by integrating Multimodal data Mining and data Synthe...
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The project focuses on the design, development, and implementation of an Autonomous Mobile Robot (AMR) system specifically tailored for warehouse environments. The escalating demand for efficient warehouse management,...
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The burgeoning field of the Internet of Things (IoT) demands innovative approaches to data privacy and user-centric services. This study introduces a novel cross-platform application engineered using the Flutter frame...
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ISBN:
(纸本)9798350372977;9798350372984
The burgeoning field of the Internet of Things (IoT) demands innovative approaches to data privacy and user-centric services. This study introduces a novel cross-platform application engineered using the Flutter framework, which orchestrates federated learning (FL) and natural language processing (NLP) to facilitate personalized event discovery within IoT environments. The application features an NLP-based chatbot for user interaction and employs Dendrite, a second-generation Matrix homeserver, to manage decentralized communication. Central to the system's design is the stringent upholding of data privacy: user data, including browsing history and application usage patterns, is processed locally on user devices to construct profiles that inform personalized event suggestions. The system's deployment of end-to-end encrypted communication underscores its commitment to user privacy and security. This integration of FL and NLP showcases a significant leap forward in the realm of privacy-preserving, personalized applications, charting a new course for user engagement in IoT.
Wireless Sensor Networks (WSN) that work hand in hand with IoT are crucial for contemporary smart city solutions. However, as these are dynamic and decentralized, they pose additional issues related to network data an...
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As modern engineering optimisation problems become increasingly complex, a significant number of them exhibit multimodal characteristics. This implies that there are multiple local optimal solutions and a single globa...
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This topic is based on big data analysis to construct a refined management system based on multi-source data collection, behavioural analysis, intelligent decision support, early warning and intervention. Through the ...
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Forecasting accurately the upcoming product demand is important to the retail sector and is achieved by the timely use of stock and sales strategies. The study investigates how a machine learning model based on all th...
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