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Alya Alshammari and Khalil El Hindi
The combination of collaborative deep learning and Cyber-Physical Systems (CPSs) has the potential to improve decision-making, adaptability, and efficiency in dynamic and distributed environments. However, it brings privacy, communication, and resource r...
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Jing Liu, Xuesong Hai and Keqin Li
Massive amounts of data drive the performance of deep learning models, but in practice, data resources are often highly dispersed and bound by data privacy and security concerns, making it difficult for multiple data sources to share their local data dir...
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Hanyue Xu, Kah Phooi Seng, Jeremy Smith and Li Minn Ang
In the context of smart cities, the integration of artificial intelligence (AI) and the Internet of Things (IoT) has led to the proliferation of AIoT systems, which handle vast amounts of data to enhance urban infrastructure and services. However, the co...
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Mikael Sabuhi, Petr Musilek and Cor-Paul Bezemer
As the number of machine learning applications increases, growing concerns about data privacy expose the limitations of traditional cloud-based machine learning methods that rely on centralized data collection and processing. Federated learning emerges a...
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Jing Kai Sim, Kaichao William Xu, Yuyang Jin, Zhi Yu Lee, Yi Jie Teo, Pallavi Mohan, Lihui Huang, Yuan Xie, Siyi Li, Nanying Liang, Qi Cao, Simon See, Ingrid Winkler and Yiyu Cai
An up-and-coming concept that seeks to transform how students learn about and study complex systems, as well as how industrial workers are trained, metaverse technology is characterized in this context by its use in virtual simulation and analysis. In th...
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Cristian Chindrus and Constantin-Florin Caruntu
In today?s dynamic and evolving digital landscape, safeguarding network infrastructure against cyber threats has become a paramount concern for organizations worldwide. This paper presents a novel and practical approach to enhancing cybersecurity readine...
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Ji-Yoon Kim and Chae-Kwan Lim
The electronic publication market is growing along with the electronic commerce market. Electronic publishing companies use recommendation systems to increase sales to recommend various services to consumers. However, due to data sparsity, the recommenda...
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Liangkun Yu, Xiang Sun, Rana Albelaihi and Chen Yi
Federated learning (FL) is a collaborative machine-learning (ML) framework particularly suited for ML models requiring numerous training samples, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Random Forest, in the co...
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Nuno Cid Martins, Bernardo Marques, Paulo Dias and Beatriz Sousa Santos
To fully leverage the benefits of augmented and mixed reality (AR/MR) in supporting users, it is crucial to establish a consistent and well-defined situated visualization (SV) model. SV encompasses visualizations that adapt based on context, considering ...
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Julián Conesa, Francisco José Mula, Kristin A. Bartlett, Ferran Naya and Manuel Contero
The use of Virtual Reality (VR) is growing in popularity in educational contexts. In this work, we present a novel software application based on immersive VR in which users can interact simultaneously with a model in a shared virtual scene and maintain a...
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