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1.
PLoS One ; 14(7): e0219658, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31314814

RESUMO

We introduce a rapid deterministic algorithm for identification of the most critical links which are capable of causing network disruptions. The algorithm is based on searching for the shortest cycles in the network and provides a significant time improvement compared with a common brute-force algorithm which scans the entire network. We used a simple measure, based on standard deviation, as a vulnerability measure. It takes into account the importance of nodes in particular network components. We demonstrate this approach on a real network with 734 nodes and 990 links. We found the worst scenarios for the cases with and without people living in the nodes. The evaluation of all network breakups can provide transportation planners and administrators with plenty of data for further statistical analyses. The presented approach provides an alternative approach to the recent research assessing the impacts of simultaneous interruptions of multiple links.


Assuntos
Algoritmos , Meios de Transporte , República Tcheca , Coleta de Dados , Humanos , Registros , Software , Tempo
2.
J Environ Manage ; 205: 209-214, 2018 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-28987917

RESUMO

Wildlife-vehicle collisions (WVC) amount to 11% of all registered traffic crashes in the Czech Republic causing, apart from numerous deaths and serious injuries to animals, property damage and injuries to car passengers. Odor repellents have the potential to lower the overall number of WVC and allow animals to cross roads at the same time. We tested the effectiveness of odor repellent preparation in prevention of WVC. 18 places were selected on the Czech road network where WVC were concentrated on the basis of traffic crash data. Control sections on the same road segments were also delimited in order to keep the traffic intensities constant. We applied a Before-After-Control-Impact (BACI) study design to control not only the effect of the measures but also the expected natural variations in wildlife populations over time. Data were compared before and after odor repellent installations. Wildlife carcass gathering was carried out during the spring and autumn. We also used the police crash database to supplement carcass data when no field works were carried out. 201 killed mammals (roe deer and wild boars) were identified in total over 47 months. We applied a Bayesian approach as only a limited numbers of WVC were available. A WVC decrease between 26 - 43% can be expected on the treated road sections. These numbers are, however, up to three-times lower than those claimed by producers of odor preparations.


Assuntos
Acidentes de Trânsito/prevenção & controle , Animais Selvagens , Odorantes , Animais , Teorema de Bayes , Comportamento Animal , República Tcheca , Suínos
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