Vol 51, No 6 (2017)

In this paper, we develop results related to the gradient controllability and actuators. The concept of gradient strategic actuators is characterized and applied to the gradient controllability of systems described by a hyperbolic equation. This emphasizes the spatial structure and the location of the actuator in order to achieve the gradient controllability. We combine the Hilbert uniqueness method and the characterization of the strategic actuators to solve the gradient controllability problem for the wave equation. The developed results are illustrated by many examples of specific shapes and systems.

The article considers the problem of planning computing tasks in hybrid supercomputer systems using the example of the Polytechnic Supercomputer Center. We have explored the classes of tasks using the distribution of calculations planning and shown their specific character when using hybrid supercomputer resources. With this in mind, we have developed the algorithms to optimize the use of resources of supercomputer systems. Furthermore, we have proposed an algorithm predicting task execution time taking into account the characteristics of the computation node and task parameters. Finally, after conducting the research we have compared the developed algorithms.

In the EU, the basis of the civil protection response to CBRNE, earth/disaster and humancaused accidents is the Emergency Response Coordination Center. For a fast response, two different architectures of centers of the regional system (CRS), with land and area robots, are presented and investigated. In the case of a static center, the robots are remotely controlled from the center by an operator. In this realization, the distance to the area to be investigated is restricted by the distance of possible remote control by the operator. The second one is a dynamic CBRN protection system, where the majority of CRS functions are organized on a car separate from the CRS building. By the car', the distance from the CRS to the accident place can usually be reached at the car motion speed. This is the main advantage of the dynamic system.

Multi-hop localization schemes are low cost, easy to implement and suitable for large-scale application. However, in practical applications, the performances of multi-hop localizations are often affected by anisotropic networks, such as irregular deployment of nodes and uneven distribution of nodes. The anisotropic problem makes the application of multi-hop localization limited, so we propose a new multi-hop approach for anisotropic network. This scheme constructs the mapping relation between hop-counts and physical distance and this algorithm views the process of location estimation as a regression prediction. In addition, we employ the geometric precision factor (Geometric Dilution Precision) to select the anchors, and effectively avoid the problem of the error amplification of the geometric relations of the anchors. Theoretical analysis and simulation results show that our proposed method can adapt to different environments, and the method has the advantages of small overhead, high precision without setting complex parameters.

A presynaptic inhibition function is described based on the language of Boolean algebra. A Fibonacci neuron is adduced as the equivalent of the sequential composition of such functions. Effective implementations of logic circuits are proposed. Affine transformations of necessary arguments are determined by Walsh spectral representations. The complexity of switching neural networks with dual neurons is analyzed.