Xiaobo Chen
Biographic Data
| ID | 7293924 |
|---|---|
| NAME | Xiaobo Chen |
| GIVEN NAMES | Xiaobo |
| FAMILY NAME | Chen |
| SIGNATURE | CHEN X |
| AFFILIATIONS | Shandong Institute of Business and Technology |
| ORCID | 0000-0001-9940-1637 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 8 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Reading between the lines
Evidential Multimodal Fusion Network for Trusted Pedestrian Crossing Intent Prediction
Accurate prediction of pedestrians’ behavior poses formidable challenges for autonomous vehicles in urban environments. Multimodal data, such as pedestrians’ motion data, context images, and ego vehicle speed, offer complementary and comprehensive information that can significantly enhance prediction performance. However, the previous methods, despite yielding promising results, integrate different modalities to form a uniform representation, whi…
Multibranch Attentive Transformer With Joint Temporal and Social Correlations for Traffic Agents Trajectory Prediction
Accurately predicting the future trajectories of traffic agents is paramount for autonomous unmanned systems, such as self-driving cars and mobile robotics. Extracting abundant temporal and social features from trajectory data and integrating the resulting features effectively pose great challenges for predictive models. To address these issues, this article proposes a novel multibranch attentive transformer (MBAT) trajectory prediction network f…
Composite Nonconvex Low-Rank Tensor Completion With Joint Structural Regression for Traffic Sensor Networks Data Recovery
Traffic sensor networks allow convenient collection of travel data that are of great significance for intelligent transportation systems (ITSs). However, the universality of missing data impedes the application of ITS and thus accurate missing data recovery is indispensable in practice. Typically, the global low-rankness and local spatiotemporal smoothness exist in underlying traffic tensor data. In light of this, this article proposes an improve…
Inverted U-shaped relationship between serum 25-hydroxyvitamin D concentrations and Toxoplasma gondii infection
Background Toxoplasma gondii ( T. gondii ) is a widespread zoonotic parasite transmitted through contaminated food or water. It poses a significant public health threat, especially to pregnant women and immunocompromised individuals. 25-Hydroxyvitamin D [25(OH)D] plays a critical role in regulating both innate and adaptive immune responses, particularly in its anti-infective capacity. However, the relationship between serum 25(OH)D concentrations…
Long-term care needs and hospitalization costs with long-term care insurance
Background: With the rapid aging of the population, the health needs of the older adult have increased significantly, resulting in the frequent occurrence of the "social hospitalization" problem, which has led to a rapid increase in hospitalization costs. This study investigates whether the "social hospitalization problem" arising from the long-term care needs can be solved through the implementation of long-term care insurance, thereby improving…
Prediction of energy consumption in hotel buildings via support vector machines
A myrsinol diterpene isolated from a traditional herbal medicine, LANGDU reverses multidrug resistance in breast cancer cells
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A myrsinol diterpene isolated from a traditional herbal medicine, LANGDU reverses multidrug resistance in breast cancer cells
Prediction of energy consumption in hotel buildings via support vector machines
Composite Nonconvex Low-Rank Tensor Completion With Joint Structural Regression for Traffic Sensor Networks Data Recovery
Traffic sensor networks allow convenient collection of travel data that are of great significance for intelligent transportation systems (ITSs). However, the universality of missing data impedes the application of ITS and thus accurate missing data recovery is indispensable in practice. Typically, the global low-rankness and local spatiotemporal smoothness exist in underlying traffic tensor data. In light of this, this article proposes an improve…
Inverted U-shaped relationship between serum 25-hydroxyvitamin D concentrations and Toxoplasma gondii infection
Background Toxoplasma gondii ( T. gondii ) is a widespread zoonotic parasite transmitted through contaminated food or water. It poses a significant public health threat, especially to pregnant women and immunocompromised individuals. 25-Hydroxyvitamin D [25(OH)D] plays a critical role in regulating both innate and adaptive immune responses, particularly in its anti-infective capacity. However, the relationship between serum 25(OH)D concentrations…
Long-term care needs and hospitalization costs with long-term care insurance
Background: With the rapid aging of the population, the health needs of the older adult have increased significantly, resulting in the frequent occurrence of the "social hospitalization" problem, which has led to a rapid increase in hospitalization costs. This study investigates whether the "social hospitalization problem" arising from the long-term care needs can be solved through the implementation of long-term care insurance, thereby improving…
Multibranch Attentive Transformer With Joint Temporal and Social Correlations for Traffic Agents Trajectory Prediction
Accurately predicting the future trajectories of traffic agents is paramount for autonomous unmanned systems, such as self-driving cars and mobile robotics. Extracting abundant temporal and social features from trajectory data and integrating the resulting features effectively pose great challenges for predictive models. To address these issues, this article proposes a novel multibranch attentive transformer (MBAT) trajectory prediction network f…
Reading between the lines
Evidential Multimodal Fusion Network for Trusted Pedestrian Crossing Intent Prediction
Accurate prediction of pedestrians’ behavior poses formidable challenges for autonomous vehicles in urban environments. Multimodal data, such as pedestrians’ motion data, context images, and ego vehicle speed, offer complementary and comprehensive information that can significantly enhance prediction performance. However, the previous methods, despite yielding promising results, integrate different modalities to form a uniform representation, whi…
Artificial Intelligence (4 works) · Computer Science (4 works) · Engineering (4 works) · Machine learning (4 works) · Medicine (3 works) · Cross-sectional study (2 works) · Environmental health (2 works) · Internal Medicine (2 works) · Mathematics (2 works) · Statistics (2 works)