Picture of virus under microscope

Research under the microscope...

The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs.

Strathprints serves world leading Open Access research by the University of Strathclyde, including research by the Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS), where research centres such as the Industrial Biotechnology Innovation Centre (IBioIC), the Cancer Research UK Formulation Unit, SeaBioTech and the Centre for Biophotonics are based.

Explore SIPBS research

Statistical interaction modeling of bovine herd behaviors

Stephen, B. and Dwyer, C. and Hyslop, J. and Bell, M. and Ross, D. and Kwong, K.H. and Michie, C. and Andonovic, I. (2011) Statistical interaction modeling of bovine herd behaviors. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 41 (6). pp. 820-829. ISSN 1094-6977

[img] Text (Stephen-etal-TSMC-2011-statistical-interaction-modeling-of-bovine-herd-behaviors)
Stephen_etal_TSMC_2011_statistical_interaction_modeling_of_bovine_herd_behaviors.pdf - Accepted Author Manuscript

Download (909kB)

Abstract

While there has been interest in modeling the group behavior of herds or flocks, much of this work has focused on simulating their collective spatial motion patterns which have not accounted for individuality in the herd and instead assume a homogenized role for all members or sub-groups of the herd. Animal behavior experts have noted that domestic animals exhibit behaviors that are indicative of social hierarchy: leader/follower type behaviors are present as well as dominance and subordination, aggression and rank order, and specific social affiliations may also exist. Both wild and domestic cattle are social species, and group behaviors are likely to be influenced by the expression of specific social interactions. In this paper, Global Positioning System coordinate fixes gathered from a herd of beef cows tracked in open fields over several days at a time are utilized to learn a model that focuses on the interactions within the herd as well as its overall movement. Using these data in this way explores the validity of existing group behavior models against actual herding behaviors. Domain knowledge, location geography and human observations, are utilized to explain the causes of these deviations from this idealized behavior.