A5101710780- Urban and Freight Transport Logistics
- Transportation and Mobility Innovations
- Human Mobility and Location-Based Analysis
- Traffic Prediction and Management Techniques
- Cooperative Communication and Network Coding
- Mobile Ad Hoc Networks
- Vehicle Routing Optimization Methods
- Advanced Manufacturing and Logistics Optimization
- Human Pose and Action Recognition
- Anomaly Detection Techniques and Applications
- Urban Transport and Accessibility
- Time Series Analysis and Forecasting
- Opportunistic and Delay-Tolerant Networks
- Gait Recognition and Analysis
- Neural Networks and Applications
- Information Retrieval and Search Behavior
- Mobile Crowdsensing and Crowdsourcing
- Optimization and Search Problems
- Data Quality and Management
- Speech and dialogue systems
- Music and Audio Processing
- Transportation Planning and Optimization
- Smart Parking Systems Research
- Context-Aware Activity Recognition Systems
- Video Surveillance and Tracking Methods
Jingdong (China)
2023-2025
Shenzhen University
2024-2025
Shanghai Jiao Tong University
2017-2024
Northeastern University
2024
Hong Kong Polytechnic University
2024
Inner Mongolia University
2023-2024
East China Jiaotong University
2023
Nanjing University of Posts and Telecommunications
2023
Stony Brook University
2020
Beihang University
2008-2020
The increasing availability of low-cost wearable devices and smartphones has significantly advanced the field sensor-based human activity recognition (HAR), attracting considerable research interest. One major challenges in HAR is domain shift problem cross-dataset recognition, which occurs due to variations users, device types, sensor placements between source dataset target dataset. Although adaptation methods have shown promise, they typically require access during training process, might...
In recent years, emergency last-mile logistics (ELML) have played an essential role in urban emergencies. The efficient allocation of couriers ELML is practical significance to ensure the supply materials, especially public health emergencies (PHEs). However, becomes challenging due instability demand, dynamic comprehension, and evolutional delivery environment for caused by PHEs. While existing work has delved into allocation, impact PHEs on demand-supply-delivery yet be considered. this...
Accurate road networks play a crucial role in modern mobile applications such as navigation and last-mile delivery. Most existing studies primarily focus on generating open areas like main roads avenues, but little attention has been given to the generation of community closed residential areas, which becomes more significant due growing demand for door-to-door services food This lack research is attributed challenges related sensing data availability quality. In this paper, we design novel...
The popularity of online e-commerce has promoted the rapid development last-mile logistics in recent years. In services, to ensure delivery efficiency and enhance user experience, zone is proposed perform task assignment, which a fundamental part delivery. Each courier responsible for one zone. Couriers will collect orders belonging their zones from station deliver customers. Existing partition practices consist manual experience-based static optimization-based methods, order amount...
Estimating service capabilities for logistics terminal stations is essential guiding operations adjustments to enhance customer experience. However, existing studies often focus on isolated metrics like on-time delivery or complaint rates, each reflecting a specific aspect of capabilities. To provide more comprehensive evaluation, we design AdaService, an Adaptive multi-faceted Service co-estimation framework. We begin by constructing Multi-faceted Hypergraph encode using multiple...
Logistics audience expansion, the process for logistics companies to find potential long-term customers, is one of most important tasks business growth. However, existing methods conventional expansion fall short due two significant challenges, intricate interplay multiple complex factors in scenario and emphasis on service usage instead one-time promotions. To address above limitations, we design LOGAE-TKG, a method based temporal knowledge graph, which consists three components: (i) graph...
To reduce the difficulty and enhance enthusiasm of private-owned electric vehicles (EVs) to participate in frequency regulation ancillary service market (FRASM), a decision aid model (DAM) is proposed.This paper presents three options for EV participating FRASM, i. e., base mode (BM), unidirectional charging (UCM), bidirectional charging/discharging (BCDM), based on reasonable simplification users' willingness.In BM, individual EVs will not be involved DAM assist users set optimal schemes...
In logistics service, the delivery timely rate is a key experience indicator, which highly essential to competitive advantage of express companies. Prediction on it enables intervention couriers with low predicted results in advance, thus ensuring employee productivity and customer satisfaction. Currently, few related works focus couriers’ level prediction, there are complex spatial correlations between road districts scenario, makes traditional real-time prediction approaches hard utilize....
Prediction of couriers' delivery timely rates in advance is essential to the logistics industry, enabling companies take preemptive measures ensure normal operation services. This becomes even more critical during anomaly conditions like epidemic outbreak, which rate will decline markedly and fluctuates significantly. Existing studies pay less attention scenario. Moreover, many works focusing on prediction tasks scenarios fail explicitly model abnormal events, e.g., treating external factors...
Points of Interest (POIs), such as entertainment, dining, and living, are crucial for urban planning location-based services. However, the high dynamics expensive updating costs POIs pose a key roadblock their applications. This is especially true developing countries, where active economic activities lead to frequent POI updates (e.g., merchants closing down new ones opening). Therefore, updating, i.e., detecting different names same (alias) update database, has become an urgent but...
Abstract Clothing-change person re-identification is an emerging research topic aimed at reidentifying individuals who have changed their clothing. This highly challenging and has not received sufficient attention to date. Most existing methods primarily focus on clothing features, but in real-world scenarios where change attire, the identification accuracy of conventional networks significantly decreases. The key challenge how effectively extract clothing-agnostic human features. paper...