ChartStory: Automated Partitioning, Layout, and Captioning of Charts into Comic-Style Narratives

Visual data storytelling is gaining importance as a means of presenting data-driven information or analysis results, especially to the general public. This has resulted in design principles being proposed for data-driven storytelling, and new authoring tools being created to aid such storytelling. However, data analysts typically lack...

Application of YOLOv4 Algorithm for Foreign Object Detection on a Belt Conveyor in a Low-Illumination Environment

The most common failures of belt conveyors are runout, coal piles and longitudinal tears. The detection methods for longitudinal tearing are currently not particularly effective. A key study area for minimizing longitudinal belt tears with the advancement of machine learning is how to use machine vision technology to detect foreign items on...

A Comparative Study of Deep Reinforcement Learning-based Transferable Energy Management Strategies for Hybrid Electric Vehicles

The deep reinforcement learning-based energy management strategies (EMS) have become a promising solution for hybrid electric vehicles (HEVs). When driving cycles are changed, the neural network will be retrained, which is a time-consuming and laborious task. A more efficient way of choosing EMS is to combine deep reinforcement learning (DRL)...

A novel dynamical collaborative optimization method of ship energy consumption based on a spatial and temporal distribution analysis of voyage data

It is of significant importance to optimize the energy consumption of ships in order to improve economy and reduce CO₂ emissions. However, the energy use of ships is affected by a series of navigational environmental parameters, which have certain spatial and temporal differences and variability. Therefore, the dynamic...