Research on Vehicle Network Analytic System Based on Ethernet Protocol Parsing DOI

Chenxing Ouyang,

Yue Qin,

Jixiang Zheng

et al.

Published: Nov. 28, 2023

The Internet of vehicles plays an essential role in the automobile industry. Existing network parsing tools only can complete tasks vehicle data traffic monitoring under certain conditions, but they do not fully support and analysis Some/IP or doIP protocol that is common used system. In order to solve this problem, paper proposes implements a new software solution which generate sending messages start monitoring, define model parse stream. addition, uses thread pool other methods optimize overall performance. implementation be hardware communication detection transmission monitoring. It also applied fault diagnosis optimization field.

Language: Английский

RealFusion: A reliable deep learning-based spatiotemporal fusion framework for generating seamless fine-resolution imagery DOI
Dizhou Guo,

Zhenhong Li,

Xu Gao

et al.

Remote Sensing of Environment, Journal Year: 2025, Volume and Issue: 321, P. 114689 - 114689

Published: March 5, 2025

Language: Английский

Citations

0
Integrating Satellite Imagery and Infield Sensors for Daily Spatial Plant Evapotranspiration Prediction: A Machine Learning-Driven Approach DOI

Farshina Nazrul Shimim,

Ethan M. Glenn,

Shilan Felegari

et al.

2022 Intermountain Engineering, Technology and Computing (IETC), Journal Year: 2024, Volume and Issue: unknown, P. 162 - 167

Published: May 13, 2024

Language: Английский

Citations

1
TEMCA-Net: A Texture-Enhanced Deep Learning Network for Automatic Solar Panel Extraction in High Groundwater Table Mining Areas DOI Creative Commons
Min Tan, Weiqiang Luo, Jingjing Li

et al.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Journal Year: 2023, Volume and Issue: 17, P. 2838 - 2848

Published: Dec. 27, 2023

Long-term coal mining has led to a series of ecological problems, constraining society's sustainable development. Ecological restoration is crucial component achieving sustainability, and with the continuous advancement photovoltaic technology, comprehensive utilization photovoltaics become one important methods in areas. The area location solar panels, as key indicators for assessing approach, require precise extraction positioning. This paper proposes Texture-Enhanced Multi-Context Attention Network (TEMCA-Net). In encoding part, network utilizes residual connections (RN) conjunction Convolutional Block Module (CBAM) preliminarily extract contextual information. Then, low-level features were input into Statistical Texture Learning (STL) texture enhancement module high-level Horizontal Atrous Spatial Pyramid Pooling (H-ASPP) module. decoding processed by H-ASPP combined texture-enhanced from STL Experiments conducted Peibei Mining Region located Xuzhou City, Jiangsu Province. We established SPPMR (Solar Panels Region) dataset. Experimental results on dataset demonstrate TEMCA-Net's outstanding performance panel extraction, precision at 90.24%, recall 93.07%, an F1-Score 91.63%, mean Intersection over Union (mIoU) 92.21%. It significantly outperforms three classic deep learning networks: Deeplabv3+, U-net, PSPnet. summary, this study provides efficient feasible solution panels areas high water tables.

Language: Английский

Citations

3
Research on Vehicle Network Analytic System Based on Ethernet Protocol Parsing DOI

Chenxing Ouyang,

Yue Qin,

Jixiang Zheng

et al.

Published: Nov. 28, 2023

The Internet of vehicles plays an essential role in the automobile industry. Existing network parsing tools only can complete tasks vehicle data traffic monitoring under certain conditions, but they do not fully support and analysis Some/IP or doIP protocol that is common used system. In order to solve this problem, paper proposes implements a new software solution which generate sending messages start monitoring, define model parse stream. addition, uses thread pool other methods optimize overall performance. implementation be hardware communication detection transmission monitoring. It also applied fault diagnosis optimization field.

Language: Английский

Citations

0