Matching images and text with multi-modal tensor fusion and re-ranking

A major challenge in matching images and text is that they have intrinsically different data distributions and feature representations. Most existing approaches are based either on embedding or classification, the first one mapping image and text instances into a common embedding space for distance measuring, and the second one regarding...

Analysis of Injury Severity of Drivers Involved Different Types of Two-Vehicle Crashes Using Random-Parameters Logit Models with Heterogeneity in Means and Variances

This study proposes random-parameters multinomial logit models, with heterogeneity in means and variances, to explore the differences in the factors influencing injury severities of drivers involved in different types of two-vehicle crashes. The models are verified using crash data from the United Kingdom (UK) over three years (2016–2018). Three...

Geographical spatial analysis and risk prediction based on machine learning for maritime traffic accidents: A case study of Fujian sea area

Safety analysis according to the spatial distribution characteristics of maritime traffic accidents is critical to maritime traffic safety management. An accident analysis framework based on the geographic information system (GIS) is proposed to characterize the spatial distribution of maritime traffic accidents occurring in the Fujian sea area...

Dreaming the wrong dream: An exploratory case study of a policy change toward sustainable urban development in a medium-sized Chinese city

Sustainable urban transformation has become a mantra for Chinese cities. While most studies focus on sustainable urbanization in megacities, the far larger number of medium-sized cities is understudied, although the latter face more severe urban problems. This article develops a framework for examining policy change in sustainable urban...

Estimating intercity heavy truck mobility flows using the deep gravity framework

Accurate estimation of intercity heavy truck mobility flows is of vital importance to urban planning, transportation management and logistics operations. The inaccessibility of big data related to intercity transport systems and the heterogeneity of trucking activities pose challenges for the reliable estimation. Recently, the advance of...