Using Sparse Parts in Fused Information to Enhance Performance in Latent Low-Rank Representation-Based Fusion of Visible and Infrared Images.

Latent Low-Rank Representation (LatLRR) has emerged as a prominent approach for fusing visible and infrared images. In this approach, images are decomposed into three fundamental components: the base part, salient part, and sparse part. The aim is to blend the base and salient features to reconstruct images accurately.

PM2.5 Concentration Prediction Model: A CNN-RF Ensemble Framework.

Although many machine learning methods have been widely used to predict PM2.5 concentrations, these single or hybrid methods still have some shortcomings. This study integrated the advantages of convolutional neural network (CNN) feature extraction and the regression ability of random forest (RF) to propose a novel CNN-RF ensemble framework for PM2.

Automatic Management and Monitoring of Bridge Lifting: A Method of Changing Engineering in Real-Time.

In recent years, owing to the increase of extreme climate events due to global climate change, the foundational erosion of old bridges has become increasingly serious. When typhoons have approached, bridge foundations have been broken due to the insufficient bearing capacity of the bridge column. The bridge bottoming method involves rebuilding the lower structure while keeping the bridge surface open, and transferring the load of the bridge temporarily to the temporary support frame to remove the bridge base or damaged part with insufficient strength.

Online community collaborative map: A geospatial and data visualization tool for cancer data.

The aim of this study was to develop an online collaborative map to enable researchers to locate, explore, and share cancer data.This 2-scale (global and country-level) cancer map adopts a database-driven model, which was implemented using the Google Map Application Programming Interface (API) and asynchronous JavaScript and XML (AJAX) technology. Seven visualization techniques were used to present data.

Integrating geographical information and augmented reality techniques for mobile escape guidelines on nuclear accident sites.

During nuclear accidents, when radioactive materials spread into the environment, the people in the affected areas should evacuate immediately. However, few information systems are available regarding escape guidelines for nuclear accidents. Therefore, this study constructs escape guidelines on mobile phones.