Toward Improved Real-Time Rainfall Intensity Estimation Using Video Surveillance Cameras

Under global climate change, urban flooding occurs frequently, leading to huge economic losses and human casualties. Extreme rainfall is one of the direct and key causes of urban flooding, and accurate rainfall estimates at high spatiotemporal resolution are of great significance for real-time urban flood forecasting. Using existing rainfall...

Rapid extraction of pavement aggregate gradation based on point clouds using deep learning networks

Usage of asphalt mixture with poor gradation will most likely lead to pavement deficiency. There is a growing need for rapid and non-destructive methods to extract pavement aggregate gradation. In this study, a deep learning-based method that utilizes point clouds data for gradation extraction was proposed. Firstly, a data enhancement...

A novel GA-LSTM-based prediction method of ship energy usage based on the characteristics analysis of operational data

Optimization of ship energy efficiency is an efficient measure to decrease fuel usage and emissions in the shipping industry. The accurate prediction model of ship energy usage is the basis to achieve optimization of ship energy efficiency. This study investigates the sequential properties of the actual voyage data from a VLOC. On this basis,...

Cross-category prediction of corrosion inhibitor performance based on molecular graph structures via a three-level message passing neural network model

Current experimental verification, computational modeling, and machine learning methods for predicting corrosion inhibition efficiency (IE) are limited to specific inhibitor categories with high cost and poor generalization. In this study, a cross-category corrosion inhibitor dataset is constructed and a three-level direct message passing...

Hardware Spiking Neural Network based Sbox AES

Hardware cryptographic algorithm implementation is easy to attack by side-channel attacks. The power-based side-channel attacks are powerful among several side-channel attacks. This attack methods use the relationship between the leakage model and power traces to reveal the secret key. Some existing countermeasures like mask and hide can protect...

GReS: Workshop on graph neural networks for recommendation and search

Graph neural networks (GNNs) have recently gained significant momentum in the recommendation community, demonstrating state-of-the-art performance in top-k recommendation and next-item recommendation. Despite promising results on GNN-based recommendation and search, most of the current GNN research remains essentially concentrated on more...

Classification of airborne laser scanning point cloud using point-based convolutional neural network

In various applications of airborne laser scanning (ALS), the classification of the point cloud is a basic and key step. It requires assigning category labels to each point, such as ground, building or vegetation. Convolutional neural networks have achieved great success in image classification and semantic segmentation, but they cannot be...

Hazardous Source Estimation Using an Artificial Neural Network, Particle Swarm Optimization and a Simulated Annealing Algorithm

Locating and quantifying the emission source plays a significant role in the emergency management of hazardous gas leak accidents. Due to the lack of a desirable atmospheric dispersion model, current source estimation algorithms cannot meet the requirements of both accuracy and efficiency. In addition, the original optimization algorithm can...