Scan Science and Technology
Contact Leading Edge Experts & Companies
Active Node
The Experts below are selected from a list of 303 Experts worldwide ranked by ideXlab platform
I J Wassell – One of the best experts on this subject based on the ideXlab platform.
-
Optimized Node Selection for Compressive Sleeping Wireless Sensor Networks
IEEE Transactions on Vehicular Technology, 2016Co-Authors: Wei Chen, I J WassellAbstract:In this paper, we propose an Active Node selection framework for compressive sleeping wireless sensor networks (WSNs) to improve signal acquisition performance, network lifetime, and the use of spectrum resources. While conventional compressive sleeping WSNs only exploit the spatial correlation of sensor Nodes, the proposed approach further exploits the temporal correlation by selecting Active Nodes using the support of the data reconstructed in the previous time instant. The Node selection problem is framed as the design of a specialized sensing matrix, where the sensing matrix consists of selected rows of an identity matrix. By capitalizing on a genie-aided reconstruction procedure, we formulate the Active Node selection problem into an optimization problem, which is then approximated by a constrained convex relaxation plus a rounding scheme. Simulation results show that our proposed Active Node selection approach leads to an improved reconstruction performance, network lifetime, and spectrum usage, in comparison to various Node selection schemes for compressive sleeping WSNs.
-
compressive sleeping wireless sensor networks with Active Node selection
Global Communications Conference, 2014Co-Authors: Wei Chen, I J WassellAbstract:In this paper, we propose an Active Node selection framework for compressive sleeping wireless sensor networks (WSNs) in order to improve the signal acquisition performance and network lifetime. The Node selection can be seen as a specialized sensing matrix design problem where the sensing matrix consists of selected rows of an identity matrix. By capitalizing on a genie-aided reconstruction procedure, we formulate the Active Node selection problem into an optimization problem, which is then approximated by a constrained convex relaxation plus a rounding scheme. The proposed approach also exploits the partially known signal support, which can be obtained from the previous signal reconstruction. Simulation results show that our proposed Active Node selection approach leads to an improved reconstruction performance and network lifetime in comparison to various Node selection schemes for compressive sleeping WSNs.
-
GLOBECOM – Compressive sleeping wireless sensor networks with Active Node selection
2014 IEEE Global Communications Conference, 2014Co-Authors: Wei Chen, I J WassellAbstract:This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/GLOCOM.2014.703677
Wei Chen – One of the best experts on this subject based on the ideXlab platform.
-
Optimized Node Selection for Compressive Sleeping Wireless Sensor Networks
IEEE Transactions on Vehicular Technology, 2016Co-Authors: Wei Chen, I J WassellAbstract:In this paper, we propose an Active Node selection framework for compressive sleeping wireless sensor networks (WSNs) to improve signal acquisition performance, network lifetime, and the use of spectrum resources. While conventional compressive sleeping WSNs only exploit the spatial correlation of sensor Nodes, the proposed approach further exploits the temporal correlation by selecting Active Nodes using the support of the data reconstructed in the previous time instant. The Node selection problem is framed as the design of a specialized sensing matrix, where the sensing matrix consists of selected rows of an identity matrix. By capitalizing on a genie-aided reconstruction procedure, we formulate the Active Node selection problem into an optimization problem, which is then approximated by a constrained convex relaxation plus a rounding scheme. Simulation results show that our proposed Active Node selection approach leads to an improved reconstruction performance, network lifetime, and spectrum usage, in comparison to various Node selection schemes for compressive sleeping WSNs.
-
compressive sleeping wireless sensor networks with Active Node selection
Global Communications Conference, 2014Co-Authors: Wei Chen, I J WassellAbstract:In this paper, we propose an Active Node selection framework for compressive sleeping wireless sensor networks (WSNs) in order to improve the signal acquisition performance and network lifetime. The Node selection can be seen as a specialized sensing matrix design problem where the sensing matrix consists of selected rows of an identity matrix. By capitalizing on a genie-aided reconstruction procedure, we formulate the Active Node selection problem into an optimization problem, which is then approximated by a constrained convex relaxation plus a rounding scheme. The proposed approach also exploits the partially known signal support, which can be obtained from the previous signal reconstruction. Simulation results show that our proposed Active Node selection approach leads to an improved reconstruction performance and network lifetime in comparison to various Node selection schemes for compressive sleeping WSNs.
-
GLOBECOM – Compressive sleeping wireless sensor networks with Active Node selection
2014 IEEE Global Communications Conference, 2014Co-Authors: Wei Chen, I J WassellAbstract:This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/GLOCOM.2014.703677
Jun Kimura – One of the best experts on this subject based on the ideXlab platform.
-
the physiological effect of anti gm1 antibodies on saltatory conduction and transmembrane currents in single motor axons
Brain, 1997Co-Authors: Nobuyuki Hirota, Ryuji Kaji, Hugh Bostock, Katsuro Shindo, Teruaki Kawasaki, Kotaro Mizutani, Nobuo Kohara, Takahiko Saida, Jun KimuraAbstract:Anti-ganglioside (anti-GM1) antibodies have been implicated in the pathogenesis of Guillain-Barre syndrome, multifocal motor neuropathy and motor neuron diseases. It has been held that they may interfere with saltatory conduction by blocking sodium channels. We tested this hypothesis by analysing action potentials from 140 single nerve fibres in 22 rat ventral roots using external longitudinal current measurement. High-titre anti-GM1 sera from Guillain-Barre syndrome or multifocal motor neuropathy patients, or anti-GM1 rabbit sera were applied to the rat ventral root, where saltatory conduction in single motor fibres was serially observed for 4-12 h (mean 8.2 h). For control experiments, we also tested anti-galactocerebroside (anti-GalC) sera, which causes acute demyelinative conduction block, and tetrodotoxin (TTX), a sodium channel blocker. Conduction block was found in 82% of the fibres treated with anti-GalC sera and 100% treated with TTX, but only in 2% (one out of 44) treated with the patients’ sera and 5% (two out of 38) treated with rabbit anti-GM1 sera. All the Nodes blocked by anti-GM1 sera revealed intense passive outward membrane current, in the interNode just beyond the last Active Node. This pattern of current flow was similar to that in fibres blocked by demyelination with anti-GalC sera, and quite different from that seen in fibres blocked by reducing sodium currents with TTX. Our findings suggest that anti-GM1 sera neither mediate conduction block nor block sodium channels on their own. We conclude that physiological action of the antibody alone is insufficient to explain clinically observed conduction block in human diseases.
-
The physiological effect of anti-GM1 antibodies on saltatory conduction and transmembrane currents in single motor axons.
Brain : a journal of neurology, 1997Co-Authors: Nobuyuki Hirota, Ryuji Kaji, Hugh Bostock, Katsuro Shindo, Teruaki Kawasaki, Kotaro Mizutani, Nobuo Kohara, Takahiko Saida, Jun KimuraAbstract:Anti-ganglioside (anti-GM1) antibodies have been implicated in the pathogenesis of Guillain-Barré syndrome, multifocal motor neuropathy and motor neuron diseases. It has been held that they may interfere with saltatory conduction by blocking sodium channels. We tested this hypothesis by analysing action potentials from 140 single nerve fibres in 22 rat ventral roots using external longitudinal current measurement. High-titre anti-GM1 sera from Guillain-Barré syndrome or multifocal motor neuropathy patients, or anti-GM1 rabbit sera were applied to the rat ventral root, where saltatory conduction in single motor fibres was serially observed for 4-12 h (mean 8.2 h). For control experiments, we also tested anti-galactocerebroside (anti-GalC) sera, which causes acute demyelinative conduction block, and tetrodotoxin (TTX), a sodium channel blocker. Conduction block was found in 82% of the fibres treated with anti-GalC sera and 100% treated with TTX, but only in 2% (one out of 44) treated with the patients’ sera and 5% (two out of 38) treated with rabbit anti-GM1 sera. All the Nodes blocked by anti-GM1 sera revealed intense passive outward membrane current, in the interNode just beyond the last Active Node. This pattern of current flow was similar to that in fibres blocked by demyelination with anti-GalC sera, and quite different from that seen in fibres blocked by reducing sodium currents with TTX. Our findings suggest that anti-GM1 sera neither mediate conduction block nor block sodium channels on their own. We conclude that physiological action of the antibody alone is insufficient to explain clinically observed conduction block in human diseases.