The Experts below are selected from a list of 205305 Experts worldwide ranked by ideXlab platform
Nir S Gov - One of the best experts on this subject based on the ideXlab platform.
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long range acoustic interactions in insect swarms an adaptive Gravity Model
New Journal of Physics, 2016Co-Authors: Dan Gorbonos, Reuven Ianconescu, James G Puckett, Nicholas T Ouellette, Nir S GovAbstract:The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. Here, we consider mating swarms of midges, which are thought to interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a Model for swarm behavior. By accounting for the adaptive nature of the midges' acoustic sensing, we show that our 'adaptive Gravity' Model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. Additionally, the adaptive interactions that we present here open a new class of equations of motion, which may appear in other biological contexts.
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long range acoustic interactions in insect swarms an adaptive Gravity Model
arXiv: Biological Physics, 2015Co-Authors: Dan Gorbonos, Reuven Ianconescu, James G Puckett, Nicholas T Ouellette, Nir S GovAbstract:The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. Here, we consider mating swarms of midges, which interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a Model for swarm behavior. By accounting for the adaptive nature of the midges' acoustic sensing, we show that our "adaptive Gravity" Model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. The adaptive interactions that we present here open a new class of equations of motion, which may appear in other biological contexts.
Reuven Ianconescu - One of the best experts on this subject based on the ideXlab platform.
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long range acoustic interactions in insect swarms an adaptive Gravity Model
New Journal of Physics, 2016Co-Authors: Dan Gorbonos, Reuven Ianconescu, James G Puckett, Nicholas T Ouellette, Nir S GovAbstract:The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. Here, we consider mating swarms of midges, which are thought to interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a Model for swarm behavior. By accounting for the adaptive nature of the midges' acoustic sensing, we show that our 'adaptive Gravity' Model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. Additionally, the adaptive interactions that we present here open a new class of equations of motion, which may appear in other biological contexts.
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long range acoustic interactions in insect swarms an adaptive Gravity Model
arXiv: Biological Physics, 2015Co-Authors: Dan Gorbonos, Reuven Ianconescu, James G Puckett, Nicholas T Ouellette, Nir S GovAbstract:The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. Here, we consider mating swarms of midges, which interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a Model for swarm behavior. By accounting for the adaptive nature of the midges' acoustic sensing, we show that our "adaptive Gravity" Model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. The adaptive interactions that we present here open a new class of equations of motion, which may appear in other biological contexts.
I M Navon - One of the best experts on this subject based on the ideXlab platform.
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an optimizing reduced order fds for the tropical pacific ocean reduced Gravity Model
International Journal for Numerical Methods in Fluids, 2007Co-Authors: Zhendong Luo, Jing Chen, Jiang Zhu, Ruiwen Wang, I M NavonAbstract:SUMMARY Proper orthogonal decomposition (POD) and singular value decomposition (SVD) methods are used to study a finite difference discretization scheme (FDS) for the tropical Pacific Ocean reduced Gravity Model. Ensembles of data are compiled from transient solutions computed from the discrete equation system derived by FDS for the tropical Pacific Ocean reduced Gravity Model. The optimal orthogonal bases are used to reconstruct the elements of the ensemble with POD and SVD. Combining the above approach with a Galerkin projection procedure yields a new optimizing FDS Model of lower dimensions and high accuracy for the tropical Pacific Ocean reduced Gravity Model. An error estimate of the new reduced order optimizing FDS Model is then derived. Numerical examples are presented illustrating that the error between the POD approximate solution and the full FDS solution is consistent with previously obtained theoretical results, thus validating the feasibility and efficiency of POD method. Copyright q 2007 John Wiley & Sons, Ltd.
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proper orthogonal decomposition approach and error estimation of mixed finite element methods for the tropical pacific ocean reduced Gravity Model
Computer Methods in Applied Mechanics and Engineering, 2007Co-Authors: Zhendong Luo, Jiang Zhu, Ruiwen Wang, I M NavonAbstract:In this paper, the tropical Pacific Ocean reduced Gravity Model is studied using the proper orthogonal decomposition (POD) technique of mixed finite element (MFE) method and an error estimate of POD approximate solution based on MFE method is derived. POD is a Model reduction technique for the simulation of physical processes governed by partial differential equations, e.g., fluid flows or other complex flow phenomena. It is shown by numerical examples that the error between POD approximate solution and reference solution is consistent with theoretical results, thus validating the feasibility and efficiency of POD method.
Dan Gorbonos - One of the best experts on this subject based on the ideXlab platform.
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long range acoustic interactions in insect swarms an adaptive Gravity Model
New Journal of Physics, 2016Co-Authors: Dan Gorbonos, Reuven Ianconescu, James G Puckett, Nicholas T Ouellette, Nir S GovAbstract:The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. Here, we consider mating swarms of midges, which are thought to interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a Model for swarm behavior. By accounting for the adaptive nature of the midges' acoustic sensing, we show that our 'adaptive Gravity' Model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. Additionally, the adaptive interactions that we present here open a new class of equations of motion, which may appear in other biological contexts.
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long range acoustic interactions in insect swarms an adaptive Gravity Model
arXiv: Biological Physics, 2015Co-Authors: Dan Gorbonos, Reuven Ianconescu, James G Puckett, Nicholas T Ouellette, Nir S GovAbstract:The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. Here, we consider mating swarms of midges, which interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a Model for swarm behavior. By accounting for the adaptive nature of the midges' acoustic sensing, we show that our "adaptive Gravity" Model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. The adaptive interactions that we present here open a new class of equations of motion, which may appear in other biological contexts.
Zhendong Luo - One of the best experts on this subject based on the ideXlab platform.
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an optimizing reduced order fds for the tropical pacific ocean reduced Gravity Model
International Journal for Numerical Methods in Fluids, 2007Co-Authors: Zhendong Luo, Jing Chen, Jiang Zhu, Ruiwen Wang, I M NavonAbstract:SUMMARY Proper orthogonal decomposition (POD) and singular value decomposition (SVD) methods are used to study a finite difference discretization scheme (FDS) for the tropical Pacific Ocean reduced Gravity Model. Ensembles of data are compiled from transient solutions computed from the discrete equation system derived by FDS for the tropical Pacific Ocean reduced Gravity Model. The optimal orthogonal bases are used to reconstruct the elements of the ensemble with POD and SVD. Combining the above approach with a Galerkin projection procedure yields a new optimizing FDS Model of lower dimensions and high accuracy for the tropical Pacific Ocean reduced Gravity Model. An error estimate of the new reduced order optimizing FDS Model is then derived. Numerical examples are presented illustrating that the error between the POD approximate solution and the full FDS solution is consistent with previously obtained theoretical results, thus validating the feasibility and efficiency of POD method. Copyright q 2007 John Wiley & Sons, Ltd.
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proper orthogonal decomposition approach and error estimation of mixed finite element methods for the tropical pacific ocean reduced Gravity Model
Computer Methods in Applied Mechanics and Engineering, 2007Co-Authors: Zhendong Luo, Jiang Zhu, Ruiwen Wang, I M NavonAbstract:In this paper, the tropical Pacific Ocean reduced Gravity Model is studied using the proper orthogonal decomposition (POD) technique of mixed finite element (MFE) method and an error estimate of POD approximate solution based on MFE method is derived. POD is a Model reduction technique for the simulation of physical processes governed by partial differential equations, e.g., fluid flows or other complex flow phenomena. It is shown by numerical examples that the error between POD approximate solution and reference solution is consistent with theoretical results, thus validating the feasibility and efficiency of POD method.
