Results 101 to 110 of about 633,122 (260)

Next app prediction based on graph neural networks and self-attention enhancement

Scientific Reports
Next mobile app prediction aims to recommend the apps that users will most likely to use next based on their historical usage behavior. It is critical for optimizing app preloading strategies and personalized recommendations, enhancing the user ...
Junxin Chen, Zhiqiong Liu, Jing Liu, Wang Li, Chang Wang   +4 more
doaj   +1 more source

St. Cloud State campus [1956?]

, 1956
Black and white aerial view of the St. Cloud State University campus taken ca.
St. Cloud State University
core  

A State‐Adaptive Koopman Control Framework for Real‐Time Deformable Tool Manipulation in Robotic Environmental Swabbing

Advanced Robotics Research, EarlyView.
This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi, Amirreza Davar, Dongyi Wang   +2 more
wiley   +1 more source

St. Cloud State campus [1965]

, 1965
Black and white aerial view of the St.
St. Cloud State University
core  

Multilevel Embedding and Dropout for Improved 3D Object Detection in Autonomous Driving Systems

Advanced Robotics Research, EarlyView.
A plug‐in framework for RoI‐based 3D object detectors exploits previously untapped multi‐level information within RoI features. Its novel multi‐level embedding and dropout strategy enables the detection head to generate predictions at different feature levels.
Xiaohu Lu, Hayder Radha
wiley   +1 more source

St. Cloud State campus [1963]

, 1963
Black and white aerial view of the St.
St. Cloud State University
core  

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

Quantifying the potential of cloud water resource exploitation to mitigate water scarcity in Xinjiang

Journal of Hydrology: Regional Studies
Study region: Xinjiang, Northwest China. Study focus: Water scarcity severely constrains Xinjiang’s ecological and socio-economic development. While exploiting cloud water is a strategic solution, quantifying its grid-scale impact on the Water Scarcity ...
Zepeng Tong, Yong Zeng, Mamtimin Ali, Jing Liu, Yi Chang, Jiangang Li, Xuefeng Cao, Zhanshan Ma   +7 more
doaj   +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

Advanced Robotics Research, EarlyView.
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley   +1 more source

St. Cloud State campus [1973]

, 1973
Black and white aerial view of the St.
St. Cloud State University
core