English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper addresses the problem of extracting traffic patterns from noisy and incomplete sensor data. We introduce an approach that combines the output of (particle filter based) tracking filters with GIS techniques. While tracking filters are standard tools for generating estimates of the position and velocities of individual objects over time, GIS techniques are used to extract geographic patterns from these estimates. GIS techniques also allow the integration of prior knowledge, such as coastlines and bathymetry, to enhance the quality of the extracted patterns. The approach has been applied to maritime traffic surveillance using report of the Automatic Identification System (AIS), which may be subject to GPS errors, spoofing, time delays and periods of missed detections. The results are continuous vessel tracks indicating each vessel's route, even when the update rate of messages is significantly slower

Semi-automatic Sea Lane Extraction Combining Particle Filtering (PF) and Geographic Information Systems (GIS)