No abstract

Formation problems of a system for identification, monitoring of the technical state and proactive maintenance of airfield land transport-processing machines by using diagnostic data are discussed. The main goal of development and implementation the proactive maintenance system is reliability control and operation safety of transport-processing machines. For the solution of this problem it is necessary to identify and prevent damages in proper time. It requires to assign the specific class of intermediate states named the pre- emergency state class. Logical and physical models describing changes in machine states, technological processes, geolocation, event visualization are discussed. The implementation results of the system of identification, monitoring of the technical state and remote proactive maintenance of airfield land transport-processing machines by using diagnostic data are presented.

We are developing methods of noninvasively delivering magnetic neuroparticles™ via intranasal administration followed by image-guided magnetic propulsion to selected locations in the brain. Once placed, the particles can activate neurons via vibrational motion or magnetoelectric stimulation. Similar particles might be used to read out neuronal electrical pulses via spintronic or liquid-crystal magnetic interactions, for fast bidirectional brain-machine interface. We have shown that particles containing liquid crystals can be read out with magnetic resonance imaging (MRI) using embedded magnetic nanoparticles and that the signal is visible even for voltages comparable to physiological characteristics. Such particles can be moved within the brain (e.g., across midline) without causing changes to neurological firing.

The topic of this article is an off-line movement system for the mobile robots. Its main goal is to ensure their movement from one point to another in a partially determined environment with static and mobile obstacles. Several systems are described. They are calculation of the impact of a potential force field, path assessment based on a neural network, avoiding collision system and a multi-agent system architecture for detection of obstacles and mobile robot control. The article presents mobile robot agents, which process data concerning the environment, communicate with each other and allow a robot to avoid the static and dynamic obstacles. Besides that, the most important task for a robot is movement in a partially determined environment, in which the obstacles' coordinates are unknown for the system.

The paper describes the architecture and algorithm of the radio frequency identification system of mobile onboard kitchen equipment used for passenger service in civil aviation aircraft.