An Open Ended Tree

An open ended list is a well known data structure in Prolog programs. It is frequently used to represent a value changing over time, while this value is referred to from several places in the data structure of the application. A weak point in this technique is that the time complexity is linear in the number of updates to the value represented by the open ended list. In this programming pearl we present a variant of the open ended list, namely an open ended tree, with an update and access time complexity logarithmic in the number of updates to the value

Metal contaminated dredged sediment derived soils: a case of diffuse contamination

Significant areas in Flanders, Belgium exhibit moderate contamination with trace metals caused by deposition or disposal of contaminated sediments. After disposal, the sediments develop into a soil- like material, on which vegetation is planted or develops spontaneously. Behaviour, cycling and ecosystem impacts of trace metals in calcareous dredged sediment disposal sites in Flanders was investigated. Although soil physico- chemical properties favour a low metal bioavailability, pore water concentrations can be elevated compared to pore water in uncontaminated soils. While metal leaching is not considered to be of concern, several plants accumulate elevated levels of Cd and Zn in leaves. Also metal levels in soil dwelling organisms and small mammals, particularly Cd, are elevated compared to reference situations. This raises concern for an enhanced transfer of metals to the food chain. A comprehensive knowledge of metal behaviour in these sites is essential for developing appropriate management options for these sites

Fireground location understanding by semantic linking of visual objects and building information models

This paper presents an outline for improved localization and situational awareness in fire emergency situations based on semantic technology and computer vision techniques. The novelty of our methodology lies in the semantic linking of video object recognition results from visual and thermal cameras with Building Information Models (BIM). The current limitations and possibilities of certain building information streams in the context of fire safety or fire incident management are addressed in this paper. Furthermore, our data management tools match higher-level semantic metadata descriptors of BIM and deep-learning based visual object recognition and classification networks. Based on these matches, estimations can be generated of camera, objects and event positions in the BIM model, transforming it from a static source of information into a rich, dynamic data provider. Previous work has already investigated the possibilities to link BIM and low-cost point sensors for fireground understanding, but these approaches did not take into account the benefits of video analysis and recent developments in semantics and feature learning research. Finally, the strengths of the proposed approach compared to the state-of-the-art is its (semi -)automatic workflow, generic and modular setup and multi-modal strategy, which allows to automatically create situational awareness, to improve localization and to facilitate the overall fire understanding