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Abnormal traffic incidents such as traffic accidents have become a significant health and development threat with the rapid urbanization of many countries. Thus it is critically important to accurately forecast the traffic accident risks of different ...

In the rapidly evolving educational landscape, the integration of metaverse and gamification is emerging as a revolutionary approach. This paper presents the Gamified Constructivist Teaching in the Metaverse (GCTM) framework, aiming to enhance ...

Knowledge graphs (KGs) have been actively studied for pedagogical purposes. To depict the rich but latent relations among different concepts in the course textbook, increasing efforts have been proposed to construct course KGs for university ...$$$$$$

Incentive mechanisms are essential to incentive workers carrying mobile handheld devices to participate in mobile crowd sensing and finally achieve good truth discovery performance. However, malicious workers may report false or malicious data to defraud ...

Early detection of fatigue driving is pivotal for the safety of drivers and pedestrians. Traditional approaches mainly employ cameras and wearable sensors to detect fatigue features, which are intrusive to drivers. Recent advances in radio frequency (RF) ...

High myopia (HM) is a leading cause of irreversible vision loss due to its association with various ocular complications including myopic maculopathy (MM). Visual field (VF) sensitivity systematically quantifies visual function, thereby revealing ...

In recent years, radio frequency identification (RFID) technology has been applied in various fields to efficiently identify objects. Considering that identification is usually performed continuously, the latest RFID approaches use previous identification ...

Deploying deep convolutional neural network (CNN) models on ubiquitous Internet of Things (IoT) devices has attracted much attention from industry and academia since it greatly facilitates our lives by providing various rapid-response services. Due to the ...

Dynamic graphs refer to graphs whose structure dynamically changes over time. Despite the benefits of learning vertex representations (i.e., embeddings) for dynamic graphs, existing works merely view a dynamic graph as a sequence of changes within the ...

Personality recognition in text is a critical problem in classifying personality traits from the input content of users. Recent studies address this issue by fine-tuning pre-trained language models (PLMs) with additional classification heads. ...

Graph neural networks (GNNs) have emerged due to their success at modeling graph data. Yet, it is challenging for GNNs to efficiently scale to large graphs. Thus, distributed GNNs come into play. To avoid communication caused by expensive data movement ...

As a key enabler of future 5G network, Service Function Chain (SFC) forwards the traffic flow along a chain of Virtual Network Functions (VNFs) to provide network services flexibility. One of the most important problems in SFC is to deploy the VNFs and ...

Federated Learning (FL) has been widely used for distributed machine learning in edge computing. In FL, the model parameters are iteratively aggregated from the clients to a central server, which is inclined to be the communication bottleneck and single ...

Crowd flow prediction, which aims to predict the in/out flows of different areas of a city, plays a critically important role in many real-world applications including intelligent transportation systems and public safety. The challenges of this problem ...

Recent years have witnessed the development and adoption of blockchain technology in intelligent transportation systems (ITS) because of its authenticity and traceability. However, increasing ITS devices impose grand challenges in ...

This paper explores on accelerating Deep Neural Network (DNN) inference with reliability guarantee in Vehicular Edge Computing (VEC) by considering the synergistic impacts of vehicle mobility and Vehicle-to-Vehicle/Infrastructure (V2V/V2I) communications. ...

We study the distributed multi-robot navigation problem, which refers to a group of mobile robots avoiding collision with each other while navigating from their start positions to the goal positions. Existing works still suffer from two limitations: 1) ...

Epilepsy in childhood is a common neurological disorder in children. Most cases are benign childhood epilepsy, which can be controlled with medication by adaptive adjustment of the dosage of antiepileptic drugs (AEDs). Recently, reinforcement ...

Supply chain traceability refers to product tracking from the source to customers, demanding transparency, authenticity, and high efficiency. In recent years, blockchain has been widely adopted in supply chain traceability to provide transparency and ...

Personalized federated learning (PFL) has emerged as a paradigm to provide a personalized model that can fit the local data distribution of each client. One natural choice for PFL is to leverage the fast adaptation capability of meta-learning, where it ...