The study relevance lies in understanding strategic objectives' content concerning intelligent technologies’ application. The development and application of artificial intelligence in various branches of human activity carry the potential for global changes in society, which, in methodological terms, increases the relevance of considering these problems. The study of ethical problems of artificial intelligence in the concept of sustainable development of society is connected with the dynamic development of innovative artificial intelligence (AI) technologies, which are considered a process of becoming a (...) new technosubject in the context of neuroscience development. The article emphasizes that the development of artificial intelligence acts as an innovative form of technology development when a new kind of human-machine technosubject is formed. The authors identify social problems of artificial intelligence application as the digitalization of life becomes a global anthropological challenge. Innovations of artificial intelligence are directly related to a number of ethical problems, as they contribute not only to the sustainable development of society but also cause dehumanization of relations between people and society. Based on the analysis of qualitative changes in scientific and technological research, using human-machine devices is becoming inevitable. Humankind must develop ethical guidelines for the application of AI systems. (shrink)

No examination of our topic can be complete without taking into account the appearance of a new face on the "religious-political stage"—Russian Catholicism.

Algorithmic software for mathematical modeling of structural stability is considered, which is reduced to solving a partial generalized eigenvalues problem of sparse matrices, with automatic parallelization of calculations on modern parallel computers with graphics processors. Peculiarities of realization of parallel algorithms for different structures of sparse matrices are presented. The times of solving the problem of stability of composite materialsusing a three-dimensional model of "finite size fibers" on computers of different architectures are given. In mathematical modeling of physical and technical (...) processes in many cases there is a need to solve problems of algebraic problem of eigenvalues with sparse matrices of large volumes. In particular, such problems arise in the analysis of the strength of structures in civil and industrial construction, aircraft construction, electric welding, etc. The solving to these problems is to determine the eigenvalues and eigenvectors of sparse matrices of different structure. The efficiency of solving these problems largely depends on the effectiveness of mathematical modeling of the problem as a whole. Continuous growth of task parameters, calculation of more complete models of objects and processes on computers require an increase in computer productivity. High-performance computing requirements are far ahead of traditional parallel computing, even with multicore processors. High-performance computing requirements are far ahead of traditional parallel computing, even with multicore processors. Today, this problem is solved by using powerful supercomputers of hybrid architecture, such as computers with multicore processors and graphics processors, which combine MIMD and SIMD architectures. But the potential of high-performance computers can be used to the fullest only with algorithmic software that takes into account both the properties of the task and the features of the hybrid architecture. Complicating the architecture of modern high-performance supercomputers of hybrid architecture, which are actively used for mathematical modeling means a significant complication of efficient use of these resources in creating parallel algorithms and programs. here are problems with the creation of algorithmic software with automatic execution of stages of work, which are associated with the efficient use of computing resources, ways to store and process sparse matrices, analysis of the reliability of computer results. This makes it possible to significantly increase the efficiency of mathematical modeling of practical problems on modern high-performance computers, as well as free users from the problems of parallelization of complex problems. he developed algorithmic software automatically implements all stages of parallel computing and processing of sparse matrices on a hybrid computer. It was used at the Institute of Mechanics named after S.P. Tymoshenko NAS of Ukraine in modeling the strength problems of composite material. A significant improvement in the time characteristics of mathematical modeling was obtained. Problems of mathematical modeling of the properties of composite materials has an important role in designing the processes of deformation and destruction of products in various subject areas. Algorithmic software for mathematical modeling of structural stability is considered, which is reduced to solving a partial generalized problem of eigen values of sparse matrices of different structure of large orders, with automatic parallelization of calculations on modern parallel computers with graphics processors. The main methodological principles and features of implementation of parallel algorithms for different structures of sparse matrices are presented, which ensure effective implementation of multilevel parallelism of a hybrid system and reduce data exchange time during the computational process. As an example of these approaches, a hybrid algorithm of the iteration method in subspace for tape and block-diagonal matrices with a frame for computers of hybrid architecture is given. Peculiarities of data decomposition for matrices of profile structure at realization of parallel algorithms are considered. The proposed approach provides automatic determination of the required topology of the hybrid computer and the optimal amount of resources for the organization of an efficient computational process. The results of testing the developed algorithmic software for problems from the collection of the University of Florida, as well as the times of solving the problem of stability of composite materials using a three-dimensional model of "finite size fibers" on computers of different architectures. The results show a significant improvement in the time characteristics of solving problems. (shrink)

Big cities and growing industrial areas bring high risk of different kinds of pollutions which would implicate to the quality of life of the society. Discovering and monitoring of polluted areas using autonomous mobile robots is nowadays a frequently considered solution concerning both environmental and human safety problems. Being part of a distributed control system, such robots can help to improve the efficiency of the existing conventional pollution prevention systems. On the other hand, during the last decade, wireless sensor networks (...) have provoked the interest of specialists from different areas by imposing a large number of theoretical and practical challenges related to their implementation. This paper attempts to deal with both issues by presenting a possible way for building robotized WSNs that can be suitable for solving different environmental monitoring tasks. The goal is to transform the WSN into an adaptive sensor system with intelligent behavior that can be used to discover and track spots or areas where given monitored environmental parameters violate defined thresholds. The inclusion of robotized agents into the WSN structure can provide additional flexibility with respect to the installation of the network sensors and allow reliable information gathering and transfer. The proposed algorithmic methods have been tested on a pre-built laboratory prototype of a robotized WSN. The robotized agents have been built using iRobot Create mobile platforms that are additionally equipped with a single-chip computers Gumstix Verdex pro TM XL6P with various expansion modules. (shrink)