Earticle

An expert network administrator is not always stationed as disasters happen. In that case, it is desirable that a novice administrator is capable of taking part in network recovery operations as well. In this paper, aknowledge- based network management system in emergency situations is presented. We use the Active Information Resource based Network Management System (AIR-NMS) to relieve the human administrator from parts of her management tasks and present an interface that remotely can control this management system. The effectiveness of the system is demonstrated by experiments using a prototype system.

Upbringing requires an active intervention in the process of children growing up. Convergence in technology and media makes it possible to augment nurturing by making blended infrastructures with new digital resources available in learning environments at schools. A game-based provision of educationally-valuable content within a collective, virtual environment combined with an analysis of events in the game after it has been played (blended nurture environment) may help to better communicate human values especially where old-fashioned discussion methods fail or do not fulfill the promise of effective, educational institution-based methods of bringing up. This is where life sciences, psychology, media, pedagogy and technology (need to) converge.

We have been designing human interactions for some learning support system or education system. The design is based on a symbol grounding model. The model is applicable to many learning domains using virtual reality technology. The design policy is simple and compact. In order to realize the policy we use/reuse some devices from the viewpoint of virtual reality. This paper introduces basic ideas and explains several example cases based on the idea.

This study was compared the variation system of body posture condition for stability by the posture. We used a model of bio parameter on the basis of the move state in the standing posture. We compared the sway movement derived from average of the physical sensing condition. Vision condition of variation average (Vi-σAVG-AVG) was verified slightly greater at 13.746±4.05 unit. Vestibular condition of variation average (Ve-σAVG-AVG) was verified slightly larger at 7.829±1.071 unit. Somatosensory condition of variation average (So-σAVG-AVG) was verified slightly smaller at 2.592±0.538 unit. CNS condition of variation average (C-σAVG-AVG) was verified slightly larger at 0.46±0.105 unit. The valuation system will be to deduce the model of body management with falling and stroke and all that sort of things. There will be to infer a data algorithm and the evaluation of processing system.

To compare body signal, was designed the F-B function system on the body movement for the comfortable state. To detect subject of the normal state, was decided on the base of physical signal in the body movement. There are to detect the condition of Vision, Vestibular, Somatosensory and CNS. Vision condition was verified a variation of greater average (Vi-ΦAVG-AVG) was presented slightly greater at 17.424±9.65 unit. Vestibular condition was identified a variation of slightly greater average (Ve-ΦAVG-AVG) was presented at 9.068±1.478 unit. Somatosensory condition was checked a variation of smaller average (So-ΦAVG-AVG) was presented slightly smaller at 2.79±0.419 unit. CNS condition was confirmed a variation of diminutive smaller average (C-ΦAVG-AVG) was presented slightly larger at 0.557±0.153 unit. As the model depends on the F-B function system of body movement, average values of these perturbation were computed F-B function comparison data. These systems will be to infer a data algorithm and a data signal processing system for the evaluation of the stability.