One should be perceiving an information system (IS) implementation project as a major [techno]organizational transformation requiring appropriate organizational transformation management techniques. However today a larger portion of IT-project managers continue to follow IS-deterministic approach mainly concentrating on delivering IS functionality and satisfying projects constraints. As a result the importance of activities aimed at business benefits attainment is underestimated. In this article authors analyze peculiarities of IT-investment business-benefits realization, formulate the principles of IT-value extraction and argue the conceptual model for benefits management at information systems implementation projects.
This paper presents implementation of several dynamic routing algorithms designed for using in networks-on-chip based on circulant topology of type C(N; 1, s2, s3) to search for the shortest routes between nodes. The developed algorithms can be implemented as RTL state machine for choosing the direction of packets in routers. Algorithms were tested on various sets of optimal triple loop circulants and compared in terms of efficiency, speed, and resources held in memory. The relationship between efficiency and the difference between the two generatrices was obtained, and the most effective one was found – the coefficient search algorithm. For all tested circulants, algorithm shows maximum efficiency, but the execution time of this algorithm is significantly higher than its considered counterparts. In addition, the efficiency and speed of the algorithm directly depend on the chosen calculation coefficients. Compared with the classic Dijkstra algorithm, the proposed algorithms do not require calculation of the entire packet path, but determine the port number to which the packet should be sent, so that it can reach the destination node. This makes it possible to significantly simplify the structure of the network-on-chip router.
This article presents a new approach to developing an adaptive genetic optimization algorithm (MAGAMO/A) using agent modeling techniques. The peculiarity of this approach is the support of the mechanism of adaptive control of key characteristics of GA, in particular, the values of the probabilities of crossover operators and mutations, their types and other important characteristics that affect the population diversity and the rate of convergence of GA. Support for adaptive control is provided by using the mechanism of agent state charts and the specified rules of transition between the corresponding states that determine the values of the control parameters of the GA at the individual level of each agent-process. The review of the most popular GAs used for multicriteria optimization, including SPEA2, NSGA, MOEA, etc., is reviewed. The main metrics for evaluating the effectiveness of such GAs (Hypervolume, Generational Distance, distance between solutions on the Pareto boundary, etc.) are considered. The efficiency of the developed approach in the solution of optimization problems of large dimension on several test examples and in comparison with other known GA is demonstrated. The main directions of further research in the field of development of agent-oriented genetic algorithms are formulated.
In the context of the studies on natural language processing, this paper substantiates the topicality of semantic search for specialists based on natural language queries. It also states the requirements to applied computer systems aimed at solving this problem, such as the necessity to extensively use semantics of natural language and structure of an available corporate database in the process of search. The principal ideas for development of such computer systems are set forth. A significant distinguished feature of the proposed method is the usage of SK-languages (standard knowledge languages), introduced in the V. A. Fomichov’s theory of K-representations (knowledge representations), for formalizing semantics of natural language queries and for reflecting semantics of words and short word combinations in linguistic databases. The described method underpinned the design of a semantic search system ExpSearch, it was implemented in the programming language Python.
In article the problem of mechanical processes modelling of radio-electronic designs is considered. It is supposed, that the basic complexity at modelling is made by process of construction of mechanical process model. The review of existing schemes of technologies of construction of modular models is executed. More perfect scheme of the technology which efficiency is shown on a practical example is offered.
Main stages of projective model order reduction (MOR) methods for electrical circuits include model construction by Pade approximation, implementation of Krylov subspace methods for essential decrease of computational noise, application of congruent transform to save circuit passivity, using block-Krylov methods for multiport circuits and multipoint rational-Krylov algorithms to mitigate the redundancy of reduced models. The considerable drop in the redundancy was achieved by applying singular value decomposition and by adaptive choosing the expansion points to be used for the moment matching. Thus, further progress in redundancy elimination cannot be provided by the modifications improvement of basis construction algorithms, and other directions to decrease redundancy should be considered. Known methods suppose direct connection of signal sources to network ports, thus resulting in the network solutions that often cannot exist in the framework of real surrounding. Then the reduction algorithm to provide required accuracy for such solutions excessively increases the model order
The article contains key results of a consumer study that identifies the role of modern Internet technologies in the communication process for medical organizations. The results are obtained during the market research, which consisted of three parts and aimed at the formation of the structure of communication environment for medical organization with the assessment of its use effectiveness. The results of the performed consumers study for medical organization presents model that describes the way of searching and selecting a medical centre by a customer. The model highlights 6 key groups of sources of information that are important for costumers. These are recommendations of existing users received in a personal conversation, by phone; recommendations of existing users received on forums, discussions in social networks; recommendations of doctors; website on the Internet; advertising (TV, radio, Newspapers, magazines), accommodation nearby. Also the model highlights 10 groups of parameters that influence the final choice of the medical organization. These are recommendations of existing users of the medical center, friends; recommendations of doctors; reputation of the medical center; convenient location; high level of service; price for services; specific specialist; qualification of doctors; uniqueness of the services provided; advertising. Taking into account the results of the study, the full map of the communication environment of the medical organization is given. The results of the study can be implemented by Russian medical organizations.
We consider a problem of computer assisted language and pronunciation learning based on the deep learning methods and the information theory of speech perception. In order to improve the efficiency of testing of pronunciation quality, we propose to train a convolutional neural network using the best reference utterances from the user. The experimental results proved that the proposed approach is characterized by higher accuracy and word recognition speed for several acoustic models when compared to conventional techniques.
This article presents an original information-analytical system developed using parametric approximation and simulation techniques and designed for scenario forecasting the dynamics of oil production in wells. This system is implemented as a software, the core of which is a simulation model developed in an IDE AnyLogic, integrated with a database and describes the dynamics of production at each well, taking into account implemented and planned geological and technical measures (GTM). A prototype system has been successfully implemented in Russia's largest oil company and used to predict the incremental oil production around the pool of all existing wells (more than 100,000 wells in the ten-year time frame), as well as assessing the potential effect of GTM for subsequent reallocation of resources between wells.
In today's democratic digital society, the relevance of conducting open and objective voting using new information technologies is increasing. Existing solutions to practically used voting systems focus on technical and legal issues, rather than on the application of new information technologies at the voting stage. The article analyzes the problems of modern electoral systems, and based on an analysis of their shortcomings, a method, algorithms and software implementation of a voting system based on blockchain technology applications with a special software implementation of smart contracts, in which the shortcomings of existing systems are eliminated, are proposed.
The article discusses criteria for comparative assessment of different computers. Special attention is paid to such criterion as performance. There is given analysis of the of the different methods advantages and disadvantages for performance measurement.
The algorithm that implements the Branch and Bound method for solving the Traveling Salesman Problem is one of the common exact algorithms for solving it. Metaheuristic algorithms for solving this problem do not guarantee obtaining an exact solution, however they work "quickly". In order to reduce the nodes number of the generated decision tree in the Branch and Bo und method, you can use the solution obtained by the metaheuristic algorithm. By choosing a metaheuristic algorithm and its combination with the Branch and Bound method, it is possible to gain time for obtaining an exact solution. Such a choice must be confirmed by experimental data on the time efficiency of the software implementation of such a combined algorithm. This article discusses some metaheuristic algorithms and a combination of such algorithms with the classical implementation of the Branch and Bound method for solving the asymmetric Traveling Salesman Problem. The data of an experimental study of the average time of obtaining an exact solution for the range of the dimension of the problem from 30 to 45 are given, and recommendations are given on the choice of a metaheuristic algorithm.