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View article: Convergence Filters for Efficient Economic MPC of Non-dissipative Systems
Convergence Filters for Efficient Economic MPC of Non-dissipative Systems Open
This note presents a novel, efficient economic model predictive control (EMPC) scheme for non-dissipative systems subject to state and input constraints. A new conception of convergence filters is defined to address the stability issue of …
View article: Lessons from A Large Language Model-based Outdoor Trail Recommendation Chatbot with Retrieval Augmented Generation
Lessons from A Large Language Model-based Outdoor Trail Recommendation Chatbot with Retrieval Augmented Generation Open
The increasing popularity of outdoor recreational activities (such as hiking and biking) has boosted the demand for a conversational AI system to provide informative and personalized suggestion on outdoor trails. Challenges arise in respon…
View article: Micromobility Flow Prediction: A Bike Sharing Station-level Study via Multi-level Spatial-Temporal Attention Neural Network
Micromobility Flow Prediction: A Bike Sharing Station-level Study via Multi-level Spatial-Temporal Attention Neural Network Open
Efficient use of urban micromobility resources such as bike sharing is challenging due to the unbalanced station-level demand and supply, which causes the maintenance of the bike sharing systems painstaking. Prior efforts have been made on…
View article: Application of Fractional Fourier Transform and BP Neural Network in Prediction of Tumor Benignity and Malignancy
Application of Fractional Fourier Transform and BP Neural Network in Prediction of Tumor Benignity and Malignancy Open
To address the limitations of traditional tumor diagnostic methods in image feature extraction and model generalization, this study innovatively proposes a synergistic diagnostic model that integrates fractional Fourier transform (FrFT) an…
View article: Toward Ubiquitous Interaction-Attentive and Extreme-Aware Crowd Activity Level Prediction
Toward Ubiquitous Interaction-Attentive and Extreme-Aware Crowd Activity Level Prediction Open
Accurate prediction of citywide crowd activity levels (CALs), i.e., the numbers of participants of citywide crowd activities under different venue categories at certain time and locations, is essential for the city management, the personal…
View article: Driver Maneuver Interaction Identification with Anomaly-Aware Federated Learning on Heterogeneous Feature Representations
Driver Maneuver Interaction Identification with Anomaly-Aware Federated Learning on Heterogeneous Feature Representations Open
Driver maneuver interaction learning (DMIL) refers to the classification task with the goal of identifying different driver-vehicle maneuver interactions (e.g., left/right turns). Existing conventional studies largely focused on the centra…
View article: Equity-Aware Cross-Graph Interactive Reinforcement Learning for Bike Station Network Expansion
Equity-Aware Cross-Graph Interactive Reinforcement Learning for Bike Station Network Expansion Open
Thanks to advances in the urban big data, the bike sharing, especially station-based bike sharing, has emerged as the important first-/last-mile connectivities in many smart cities. Bike station network (BSN) expansion recommendation, i.e.…
View article: Interpretable Fake News Detection with Topic and Deep Variational Models
Interpretable Fake News Detection with Topic and Deep Variational Models Open
The growing societal dependence on social media and user generated content for news and information has increased the influence of unreliable sources and fake content, which muddles public discourse and lessens trust in the media. Validati…
View article: Towards Spatio-Temporal Cross-Platform Graph Embedding Fusion for Urban Traffic Flow Prediction
Towards Spatio-Temporal Cross-Platform Graph Embedding Fusion for Urban Traffic Flow Prediction Open
In this paper, we have proposed STC-GEF, a novel Spatio-Temporal Cross-platform Graph Embedding Fusion approach for the urban traffic flow prediction. We have designed a spatial embedding module based on graph convolutional networks (GCN) …
View article: Spatio-Temporal Graph Attention Embedding for Joint Crowd Flow and Transition Predictions
Spatio-Temporal Graph Attention Embedding for Joint Crowd Flow and Transition Predictions Open
Crowd mobility prediction, in particular, forecasting flows at and transitions across different locations, is essential for crowd analytics and management in spacious environments featured with large gathering. We propose GAEFT, a novel cr…
View article: Towards Dynamic Urban Bike Usage Prediction for Station Network Reconfiguration
Towards Dynamic Urban Bike Usage Prediction for Station Network Reconfiguration Open
Bike sharing has become one of the major choices of transportation for residents in metropolitan cities worldwide. A station-based bike sharing system is usually operated in the way that a user picks up a bike from one station, and drops i…
View article: Dynamic Flow Distribution Prediction for Urban Dockless E-Scooter Sharing Reconfiguration
Dynamic Flow Distribution Prediction for Urban Dockless E-Scooter Sharing Reconfiguration Open
Thanks to recent progresses in mobile payment, IoT, electric motors, batteries and location-based services, Dockless E-scooter Sharing (DES) has become a popular means of last-mile commute for a growing number of (smart) cities. As e-scoot…
View article: Towards Fine-grained Flow Forecasting: A Graph Attention Approach for Bike Sharing Systems
Towards Fine-grained Flow Forecasting: A Graph Attention Approach for Bike Sharing Systems Open
As a healthy, efficient and green alternative to motorized urban travel, bike sharing has been increasingly popular, leading to wide deployment and use of bikes instead of cars. Accurate bike-flow prediction at the individual station level…
View article: Spatio-Temporal Capsule-based Reinforcement Learning for Mobility-on-Demand Network Coordination
Spatio-Temporal Capsule-based Reinforcement Learning for Mobility-on-Demand Network Coordination Open
As an alternative means of convenient and smart transportation, mobility-on-demand (MOD), typified by online ride-sharing and connected taxicabs, has been rapidly growing and spreading worldwide. The large volume of complex traffic and the…
View article: Geomagnetism for Smartphone-Based Indoor Localization
Geomagnetism for Smartphone-Based Indoor Localization Open
Geomagnetism has recently attracted considerable attention for indoor localization due to its pervasiveness and independence from extra infrastructure. Its location signature has been observed to be temporally stable and spatially discerni…