This study presents the results of evaluation of the competitiveness of farmers and the agricultural sector in the region as a whole. Traditional approach of estimating monopolization level uses Herfindahl-Hirshman and Lerner indexes. But this methods not applicable in case of inhomogeneity of product in industry or when firms manufacture different type of products. The evaluation was performed by using the instruments of fuzzy set theory and the correlation analysis. This technique allows us to estimate the degree of monopolization of the industry and its sub-sectors, as well as to hold a comparative analysis and to identify trends of development. Technique consists several steps. Determine the maximum amount of product produced by any company in the sector in the period and the percentage of the volume of production from which the company can be named as leader. Fuzzy numbers of leadership are calculated for each firm's product. If the company produces more than one product, the fuzzy numbers for each product are aggregated into one by using the fuzzy operation "or". Depending on the percentage level in the industry will change and the number of companies that are recognized as leaders. Simulations proved that correlation between percentage level and number of leaders in industry depends on market structure: Monopoly, oligopoly or pure competition. Correlation coefficient tends from -1 for the monopolized industries to 0 for pure competition. We provided computer simulation to calculate the boundaries of correlation coefficient to identify types of market structure. The analysis was held according to the industrial and economic activity of all 509 agricultural enterprises and 13 types of products in Republic Tatarstan of Russian Federation during 2011-2013. The obtained results are comparable with the results of the calculation the Herfindahl-Hirschman index for each product. However, the proposed technique allows us to make a general assessment of industry's competitiveness. The technique has an applied significance in the development of government support measures.

Oil prices movements is very important macroeconomic factor for decision making. The accuracy of results for different types of oil brands depends on models and algorithms. This paper evaluates the effectiveness of using fuzzy sets to forecast daily Brent oil prices. It also contains possible modifications of the proposed method and in comparison with basic methods. The results suggest that Brent oil prices series have short memory because using information about last 2-days prices shows better forecast accuracy. Forecasting based on fixed universe of discourse shows better efficiency and it also proves that oil prices series has short memory. Adding the probability of switching between linguistic terms in defuzzification function could be used to improve accuracy of predictions. Also the approach can take into consideration expert's opinion about direction of future variation. The effective expert's work can reduce errors of forecast from 1.5% till 0.76%. But this modification can be used if experts correctly guess the direction of the change in trend in eight out of ten cases and more. The reasonable obtained results can be used by analysts dealing with the prediction of oil prices.

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A general method is proposed to synthesize digital devices in order to perform discrete orthogonal transformations (DOT) on programmable logic integrated circuits (PLIC) of FPGA class. The basic and the most "slow" operation during DOT performance is the operation of multiplying by a constant factor (constant)-OMC. To perform DOT digital devices are implemented at the use of the same type of IP-cores, which allow to realize OMC. According to the proposed method, OMC is determined on the basis of picturing set over the elements of the Galois field. Due to the distributed computing of nonlinear polynomial function systems defined over the Galois field in PLIC/FPGA architecture, the reduction in the estimates of time complexity concerning OMC performance is achieved. Each non-linear polynomial function, like OMC, is realized on the basis of the same type of IP-cores according to one of the structural schemes in accordance with the requirements for the device to perform DOT. The use of IP cores significantly reduces the cost of designing a device that implements DOT in the PLIC/FPGA architecture.