Gait analysis plays a pivotal role in the detection and monitoring of Parkinson’s disease (PD), offering insights into motor impairments characteristic of the condition. This study proposes a novel approach employing...
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In this paper, we present a Federated Learning-based Intrusion Detection System (FL-IDS) aimed at enhancing security in Connected Autonomous Vehicles (CAVs) within IoT environments. The novelty lies in the dual utiliz...
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In this paper, we present a Federated Learning-based Intrusion Detection System (FL-IDS) aimed at enhancing security in Connected Autonomous Vehicles (CAVs) within IoT environments. The novelty lies in the dual utilization of Support Vector Machine (SVM) and Convolutional Neural Networks (CNN) for anomaly detection, leveraging the Flower framework for privacy-preserving, decentralized model training. Unlike traditional centralized approaches, FL-IDS ensures data confidentiality by sharing only model updates. Using the NSL-KDD dataset, our evaluation highlights superior accuracy and loss metrics, validating the efficiency of both machine learning and deep learning methods for detecting DDoS, Probe, and U2R attacks. This work contributes to the advancement of secure and efficient vehicular communication systems, providing scalable solutions for real-world IoT deployments.
In this paper, we present the first implementation of a social robot acting as a companion for individuals eating alone. Our system can engage in multimodal interactions with the user during meals. It conducts convers...
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Learning composite concepts, such as "red car", from individual examples—like a white car representing the concept of "car" and a red strawberry representing the concept of "red"—is inh...
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The growing use of drones in logistics, agriculture, surveillance, and search-and-rescue operations has highlighted the need for more intuitive and adaptable control systems. Traditional control methods, such as joyst...
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Lung cancer remains a leading cause of mortality, affecting both men and women, has posed significant challenges for accurate identification for decades. Recent advancements in Deep Learning (DL) have revolutionized t...
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This paper proposes a framework for real-time monitoring of the power consumption of distributed calculation on the nodes of the cluster. The framework allows to visualize and analyze the provider results based on the...
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Cell-free networks have emerged as a new paradigm for beyond-5G networks, offering uniform coverage and improved control over interference. However, scalability poses a challenge in full cell-free networks, where all ...
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Deep hashing retrieval has gained widespread use in big data retrieval due to its robust feature extraction and efficient hashing process. However, training advanced deep hashing models has become more expensive due t...
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With the continuous development of intelligent transportation systems (ITS), the Vehicular Ad-hoc Networks, as a core component of smart transportation, has become a crucial technology for improving traffic safety and...
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