The Experts below are selected from a list of 65073 Experts worldwide ranked by ideXlab platform

Noa Pinter-wollman - One of the best experts on this subject based on the ideXlab platform.

  • The use of multilayer network analysis in Animal Behaviour
    Animal Behaviour, 2019
    Co-Authors: Kelly R. Finn, Mason A Porter, Matthew J Silk, Noa Pinter-wollman
    Abstract:

    Network analysis has driven key developments in research on Animal Behaviour by providing quantitative methods to study the social structures of Animal groups and populations. A recent formalism, known as multilayer network analysis, has advanced the study of multifaceted networked systems in many disciplines. It offers novel ways to study and quantify Animal Behaviour through connected ‘layers’ of interactions. In this article, we review common questions in Animal Behaviour that can be studied using a multilayer approach, and we link these questions to specific analyses. We outline the types of Behavioural data and questions that may be suitable to study using multilayer network analysis. We detail several multilayer methods, which can provide new insights into questions about Animal sociality at individual, group, population and evolutionary levels of organization. We give examples for how to implement multilayer methods to demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. Finally, we discuss caveats to undertaking multilayer network analysis in the study of Animal social networks, and we call attention to methodological challenges for the application of these approaches. Our aim is to instigate the study of new questions about Animal sociality using the new toolbox of multilayer network analysis.

  • The use of multilayer network analysis in Animal Behaviour
    arXiv: Populations and Evolution, 2017
    Co-Authors: Kelly R. Finn, Mason A Porter, Matthew J Silk, Noa Pinter-wollman
    Abstract:

    Network analysis has driven key developments in research on Animal Behaviour by providing quantitative methods to study the social structures of Animal groups and populations. A recent formalism, known as \emph{multilayer network analysis}, has advanced the study of multifaceted networked systems in many disciplines. It offers novel ways to study and quantify Animal Behaviour as connected 'layers' of interactions. In this article, we review common questions in Animal Behaviour that can be studied using a multilayer approach, and we link these questions to specific analyses. We outline the types of Behavioural data and questions that may be suitable to study using multilayer network analysis. We detail several multilayer methods, which can provide new insights into questions about Animal sociality at individual, group, population, and evolutionary levels of organisation. We give examples for how to implement multilayer methods to demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. Finally, we discuss caveats to undertaking multilayer network analysis in the study of Animal social networks, and we call attention to methodological challenges for the application of these approaches. Our aim is to instigate the study of new questions about Animal sociality using the new toolbox of multilayer network analysis.

D L Swain - One of the best experts on this subject based on the ideXlab platform.

  • Animal Behaviour understanding using wireless sensor networks
    Local Computer Networks, 2006
    Co-Authors: Ying Guo, Peter Corke, G Poulton, Tim Wark, Greg Bishophurley, D L Swain
    Abstract:

    This paper presents research that is being conducted by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) with the aim of investigating the use of wireless sensor networks for automated livestock monitoring and control. It is difficult to achieve practical and reliable cattle monitoring with current conventional technologies due to challenges such as large grazing areas of cattle, long time periods of data sampling, and constantly varying physical environments. Wireless sensor networks bring a new level of possibilities into this area with the potential for greatly increased spatial and temporal resolution of measurement data. CSIRO has created a wireless sensor platform for Animal Behaviour monitoring where we are able to observe and collect information of Animals without significantly interfering with them. Based on such monitoring information, we can identify each Animal's Behaviour and activities successfully.

Peter Corke - One of the best experts on this subject based on the ideXlab platform.

  • monitoring Animal Behaviour and environmental interactions using wireless sensor networks gps collars and satellite remote sensing
    Sensors, 2009
    Co-Authors: R N Handcock, Peter Corke, Tim Wark, D L Swai, Greg Ishophurley, Kym P Patiso, Philip Valencia, Christophe J Oneill
    Abstract:

    Remote monitoring of Animal Behaviour in the environment can assist in managing both the Animal and its environmental impact. GPS collars which record Animal locations with high temporal frequency allow researchers to monitor both Animal Behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand Animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor Behavioural preferences and social Behaviour of cattle.

  • Animal Behaviour understanding using wireless sensor networks
    Local Computer Networks, 2006
    Co-Authors: Ying Guo, Peter Corke, G Poulton, Tim Wark, Greg Bishophurley, D L Swain
    Abstract:

    This paper presents research that is being conducted by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) with the aim of investigating the use of wireless sensor networks for automated livestock monitoring and control. It is difficult to achieve practical and reliable cattle monitoring with current conventional technologies due to challenges such as large grazing areas of cattle, long time periods of data sampling, and constantly varying physical environments. Wireless sensor networks bring a new level of possibilities into this area with the potential for greatly increased spatial and temporal resolution of measurement data. CSIRO has created a wireless sensor platform for Animal Behaviour monitoring where we are able to observe and collect information of Animals without significantly interfering with them. Based on such monitoring information, we can identify each Animal's Behaviour and activities successfully.

Tim Wark - One of the best experts on this subject based on the ideXlab platform.

  • monitoring Animal Behaviour and environmental interactions using wireless sensor networks gps collars and satellite remote sensing
    Sensors, 2009
    Co-Authors: R N Handcock, Peter Corke, Tim Wark, D L Swai, Greg Ishophurley, Kym P Patiso, Philip Valencia, Christophe J Oneill
    Abstract:

    Remote monitoring of Animal Behaviour in the environment can assist in managing both the Animal and its environmental impact. GPS collars which record Animal locations with high temporal frequency allow researchers to monitor both Animal Behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand Animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor Behavioural preferences and social Behaviour of cattle.

  • Animal Behaviour understanding using wireless sensor networks
    Local Computer Networks, 2006
    Co-Authors: Ying Guo, Peter Corke, G Poulton, Tim Wark, Greg Bishophurley, D L Swain
    Abstract:

    This paper presents research that is being conducted by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) with the aim of investigating the use of wireless sensor networks for automated livestock monitoring and control. It is difficult to achieve practical and reliable cattle monitoring with current conventional technologies due to challenges such as large grazing areas of cattle, long time periods of data sampling, and constantly varying physical environments. Wireless sensor networks bring a new level of possibilities into this area with the potential for greatly increased spatial and temporal resolution of measurement data. CSIRO has created a wireless sensor platform for Animal Behaviour monitoring where we are able to observe and collect information of Animals without significantly interfering with them. Based on such monitoring information, we can identify each Animal's Behaviour and activities successfully.

Kelly R. Finn - One of the best experts on this subject based on the ideXlab platform.

  • The use of multilayer network analysis in Animal Behaviour
    Animal Behaviour, 2019
    Co-Authors: Kelly R. Finn, Mason A Porter, Matthew J Silk, Noa Pinter-wollman
    Abstract:

    Network analysis has driven key developments in research on Animal Behaviour by providing quantitative methods to study the social structures of Animal groups and populations. A recent formalism, known as multilayer network analysis, has advanced the study of multifaceted networked systems in many disciplines. It offers novel ways to study and quantify Animal Behaviour through connected ‘layers’ of interactions. In this article, we review common questions in Animal Behaviour that can be studied using a multilayer approach, and we link these questions to specific analyses. We outline the types of Behavioural data and questions that may be suitable to study using multilayer network analysis. We detail several multilayer methods, which can provide new insights into questions about Animal sociality at individual, group, population and evolutionary levels of organization. We give examples for how to implement multilayer methods to demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. Finally, we discuss caveats to undertaking multilayer network analysis in the study of Animal social networks, and we call attention to methodological challenges for the application of these approaches. Our aim is to instigate the study of new questions about Animal sociality using the new toolbox of multilayer network analysis.

  • The use of multilayer network analysis in Animal Behaviour
    arXiv: Populations and Evolution, 2017
    Co-Authors: Kelly R. Finn, Mason A Porter, Matthew J Silk, Noa Pinter-wollman
    Abstract:

    Network analysis has driven key developments in research on Animal Behaviour by providing quantitative methods to study the social structures of Animal groups and populations. A recent formalism, known as \emph{multilayer network analysis}, has advanced the study of multifaceted networked systems in many disciplines. It offers novel ways to study and quantify Animal Behaviour as connected 'layers' of interactions. In this article, we review common questions in Animal Behaviour that can be studied using a multilayer approach, and we link these questions to specific analyses. We outline the types of Behavioural data and questions that may be suitable to study using multilayer network analysis. We detail several multilayer methods, which can provide new insights into questions about Animal sociality at individual, group, population, and evolutionary levels of organisation. We give examples for how to implement multilayer methods to demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. Finally, we discuss caveats to undertaking multilayer network analysis in the study of Animal social networks, and we call attention to methodological challenges for the application of these approaches. Our aim is to instigate the study of new questions about Animal sociality using the new toolbox of multilayer network analysis.