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Priority Based Routing for Forest Fire Monitoring in Wireless Sensor Network

Koga T., Toyoda K., Sasase I.

Journal of Telecommunications and Information Technology

2014

nr 3

90--97

Recently, forest fire monitoring system in wireless sensor networks has received much attention. The conventional scheme receives fire alert data quickly to inform about fire forest event. However, since two or more nodes may detect a fire, high priority fire detection data frequently collide. In this paper, a new forest fire monitoring system is proposed in order to reduce high priority fire detection data dropped rate, by specifying a high priority received data immediately after fire detection and just before the destruction by fire. Furthermore, the node only transmits high priority data to a node, which has a low possibility of destruction by fire for low end-to-end delay of high priority fire detection data. The simulation results show that proposed scheme can reduce high priority data dropped ratio and the end-to-end delay, and have less effect of wind direction compared with the conventional scheme.

A human robot interaction by a model of the emotional learning in the brain

Sonoh S., Aou S., Horio K., Tamukoh H., Koga T., Yamakawa T.

Journal of Automation Mobile Robotics and Intelligent Systems

2010

Vol. 4, No. 2

48-54

In this paper, we proposed an emotional expression system as a brain-inspired system. The emotional expression was achieved by an Emotional expression Model of the Amygdala (EMA), which was an engineering model inspired by an emotional learning in the brain. EMA can realize both recognition of sensory inputs and a classical conditioning of emotional inputs. Furthermore, a specific hardware of EMA was developed with a massively parallel architecture by using an FPGA, and achieved a calculation speed that is over 20 times faster than an embedded general-purpose computer. Finally, we confirmed an effectiveness of a human-robot interaction with the emotions, which were generated by the proposed emotional expression system.

Multiaxial constitutive modelling for R-phase and M-phase transformations of TiNi shape memory alloys

Kawai M., Ogawa H., Baburaj V., Koga T.

Archives of Mechanics

1999

Vol. 51, nr 6

665-692

A multiaxial constitutive model for describing the pseudoelastic and shape memory behaviour of a titanium-nickel (TiNi) shape memory alloy due to the stress-induced rhombohedral and martensitic transformations has been developed from a phenomenological point of view. First, the existing constitutive models proposed for shape memory alloys are reviewed in brief. On the basis of a comparison between these models, an expression prescribing the transformation strain range is proposed which depends on the applied stress and the current phase volume fraction. Then, the uniaxial Tanaka model for the rhombohedral and martensitic transformations of TiNi shape memory alloys is extended to a multiaxial form using the framework of the Boyd-Lagoudas model and the proposed expression of the transformation strain range. Finally, the capability of the present model to predict the pseudoelastic behaviour of TiNi shape memory alloys is examined through numerical simulations of stress-strain responses under uniaxial and multiaxial proportional/nonproportional loading-unloading conditions.