Search

The research is aimed at determining the deceleration factor associated with the increase in computing of a multiprocessor system. It should be noted that the research of these problems is important and relevant. The aim of the research is the further approach development associated with methodology defi nition for evaluation of the multiprocessor modular computing system effectiveness and this value impact of the computational deceleration.

This chapter draws attention to a specific feature of a NEG model that uses linear (and not iso-elastic) demand functions, namely its ability to account for zero trade. Thus, it represents a suitable framework to study how changes in parameters that are typical for NEG models, such as trade costs and regional market size, not only shape the regional distribution of economic activity, but at the same time determine the emergence of additional trade links between formerly autarkic regions. We survey some related papers and present a three-region framework that potentially nests many possible trade patterns. To focus the analysis, we study in more detail three specific trade patterns frequently found in the EU trade network. We start with three autarkic regions; then we introduce the possibility that two regions trade with each other; and, finally, we allow for one region trading with the other two, but the latter are still not trading with each other. We find a surprising plethora of long-run equilibria each involving a specific regional distribution of economic activity and a specific pattern of trade links. We show how a reduction in trade costs shapes simultaneously industry location and the configuration of the trade network.

The treaty of Rome was signed in 1957 and it started a continuous process of strengthening the internal integration of the EU. In this study, we consider the economic effects of intensified trade integration within the Union in which productive factors are also mobile. We argue that a New Economic Geography (NEG) perspective is preferable to the Heckscher-Ohlin approach. We show that trade integration leads to specialization, trade creation, and trade diversion (as predicted by a standard Heckscher-Ohlin framework), but it may also lead to agglomeration within the Union, which is typical of a NEG framework. We show that these agglomeration processes reinforce the specialization and trade effects of trade integration. Finally, we provide insights into the dynamic processes and show that the coexistence of attractors in our modeling approach is more pervasive than in a standard NEG framework.

In this paper, we put forward a four-region new economic geography footloose entrepreneur model in which regions are differentiated by their size and their geographical position along a line. There are two distinct trade blocs, each of them consisting of a pair of regions. Direct and indirect trade between all regions is allowed, whereas factor mobility can occur only between regions of the same bloc. Given this more general geographical structure, as compared to previous studies, we are able to disentangle two manifestations of the market access effect: firms can take advantage of locating both in a more central region (centrality effect) and/or in a bigger region (local market size effect). The model is able to generate a plethora of long-term outcomes, including four equilibria with full agglomeration in each trade bloc that can be ranked by factor owners. Equilibria where industry is dispersed or agglomerated in a bloc and dispersed in the other one, are also possible as well as more complex attractors. Finally, by allowing direct and indirect trade between regions, we are able to look at the effect of trade integration on transit traffic by evaluating in a preliminary analysis the consequences of policies aiming at limiting transport volumes in a model with shifting industry.

Introduction. Possible methods of pattern recognition of 2D images are described. A matched filtering method based on "in terms of level" normalization is the best way for classification of 2D images. Example of "in terms of level" normalization algorithm of 2D images. By means of example whole process of comparison of 2D images based on proposed method is presented. Proposed algorithms. Normalization algorithm of 2D reference image based on orthogonal transformation and estimation algorithm of similarity between tested and reference 2D images are proposed. Conclusions. The main advantages of the proposed method of 2D image classification are presented in conclusions. Minimization of some disadvantages is proposed., Рассмотрены методы распознавания двумерных (2D) образов. Доказано, что метод нормализации по уровню является лучшим решением при проведении классификации двумерных образов. Предложены алгоритм нормализации 2D эталонного образа при использовании ортогонального преобразования и алгоритм оценки степени подобия между исследуемым и эталонным 2D образами. При помощи приведенного примера показан весь процесс сравнения двумерных образов при помощи предложенного метода., Розглянуто методи розпізнавання двовимірних (2D) образів. Доведено, що метод нормалізації за рівнем є найкращим рішенням при проведенні класифікації двовимірних образів. Запропоновано алгоритм нормалізації 2D еталонного образу при використанні ортогонального перетворення і алгоритм оцінки ступеня подібності між досліджуваним і еталонним 2D образами. За допомогою наведеного прикладу показано увесь процес порівняння двовимірних образів за допомогою запропонованого методу.

Показано можливість використання перетворення Мелліна при класифікації образів на базі їх нормалізації або нормального перетворення при зміні масштабу аргументів досліджуваних образів відносно еталонного образу. Наведено приклад обчислень, який показав простоту застосування перетворення Мелліна. Отримана достатньо висока чутливість класифікатора до змін параметрів графоелементів досліджуваного образу відносно еталона. Introduction. Possible methods of pattern recognition are described. Transform coefficient, allowing numerically to evaluate the difference between the test and reference signal is proposed. In this case, the reference signal is selected by researcher independently, which gives more freedom. Theoretical positions. The possibility of Mellin transform using for pattern classification of images based on their normalization or normalized transformation when scale of studied images is differ from a reference image, is considered. A similar of Fourier and Mellin transforms is proved. Classification algorithm. Proposed algorithm can be used when change of scale arguments of the signals is presented. This algorithm has a clear structure that allows implement it in hardware with minimal effort. Examples. Examples of the Mellin transform using for different distortion types of the test signal are considered. The test signals have time scale and distorted form changing. The obtained sensitivity value of classifier to parameters changes of the investigated image with respect to the reference image was sufficient to get a stable work of this unit. Conclusions. The main advantages of the Mellin transform using for recognizing signals at different scales are presented is conclusions. Показана возможность использования преобразования Меллина при классификации образов на базе их нормализации или нормального преобразования при изменении масштаба аргументов исследуемых образов относительно эталонного образа. Приведен пример вычислений, показавший простоту применения преобразования Меллина. Получена достаточно высокая чувствительность классификатора к изменениям параметров исследуемого образа относительно эталона.

В статті на базі алгоритму формування матричного оператора дискретного ортогонального одновимірного перетворення створено алгоритм двовимірного перетворення. Проблема створення двовимірного перетворення полягає в великому порядку матричного оператора, якщо двовимірний образ представляється у вигляді одного рядка, утвореного послідовністю рядків (стовпців) образу. В цьому випадку для матриці образу порядку N порядок матричного оператора становить N2, тобто кількість елементів такого оператора дорівнює N4, що неприпустимо, враховуючи, що для образів N = 256…1024. Отримано просту структуру формування матричного оператора дискретного двовимірного перетворення, урахування якої дозволяє зменшити об’єм пам’яті, необхідної для обчислення коефіцієнта трансформант, до N3, що робить можливим класифікацію образів з матрицями порядку N ≈ 256…1024. Алгоритм проілюстровано на прикладі, обраному виходячи з міркувань простоти перевірки отримуваних результатів. A new 2D transformation algorithm based on algorithm of matrix operator formation in 1D discrete orthogonal transformation is presented. Complexity 2D algorithm creation is a high order of matrix operator when 2D image is presented as a sequence of rows (columns). In this case the order of matrix operator is N2 for image matrix of N order. As result, the number of its elements is equal to N4, which is equivalent of huge figure for image, having size N = 256…1024. A simple algorithm for creation of matrix operator in 2D discrete transformation was obtained. It allows reduce to N3 the memory volume, required for transform coefficient calculation. It makes possible to classify images having matrix of order N ≈ 256…1024. The algorithm is illustrated on the example selected from the ease of inspection results. В статье на базе алгоритма формирования матричного оператора дискретного ортогонального одномерного преобразования создан алгоритм двумерного преобразования. Проблема создания двумерного преобразования состоит в большом порядке матричного оператора, если двумерный образ представить в виде одной строки, образованной последовательностью строк (столбцов) образа. В этом случае для матрицы образа порядка N порядок матричного оператора равен N2, т.е. количество элементов матричного оператора равно N4, что недопустимо, учитывая, что для образов N = 256…1024. Получена простая структура формирования матричного оператора двумерного дискретного преобразования, учет которой позволяет уменьшить объем памяти, необходимой для вычисления коэффициента трансформант, до N3, что делает возможным классификацию образов с матрицами порядка N ≈ 256…1024. Алгоритм проиллюстрирован на примере, выбранном исходя из простоты проверки получаемых результатов.

Розглянуто методи розпізнавання двовимірних (2D) образів. Доведено, що метод нормалізації за рівнем є найкращим рішенням при проведенні класифікації двовимірних образів. Запропоновано алгоритм нормалізації 2D еталонного образу при використанні ортогонального перетворення і алгоритм оцінки ступеня подібності між досліджуваним і еталонним 2D образами. За допомогою наведеного прикладу показано увесь процес порівняння двовимірних образів за допомогою запропонованого методу. Introduction. Possible methods of pattern recognition of 2D images are described. Matched filtering method based on "in terms of level" normalization is the best way for classification of 2D images. Example of "in terms of level" normalization algorithm of 2D images. By means of example whole process of comparison of 2D images based on proposed method is presented. Proposed algorithms. Normalization algorithm of 2D reference image based on orthogonal transformation and estimation algorithm of similarity between tested and reference 2D images are proposed. Conclusions. The main advantages of the proposed method of 2D image classification are presented in conclusions. Minimization of some disadvantages is proposed. Рассмотрены методы распознавания двумерных (2D) образов. Доказано, что метод нормализации по уровню является лучшим решением при проведении классификации двумерных образов. Предложены алгоритм нормализации 2D эталонного образа при использовании ортогонального преобразования и алгоритм оценки степени подобия между исследуемым и эталонным 2D образами. При помощи приведенного примера показан весь процесс сравнения двумерных образов при помощи предложенного метода.

Inspired by Brexit, the paper explores the effects of splitting an integration area or "Union" on trade Patterns and the spatial distribution of industry. A linear three-region New Economic Geography (NEG) model is developed and two possible situations before separation are considered: agglomeration and dispersion. By analogy with the Brexit options, soft and hard separation scenarios are considered. Firms in the leaving region may move to the larger Union market, even on the periphery, relocation substituting trade; or firms in the Union may move in the more isolated leaving region, escaping from competition. The paper also analyses deeper Union integration following separation. Instances of multistability and complex Dynamics are found.

We consider a two-class growth model with optimal saving and switch in behavior. The dynamics of this model is described by a two-dimensional (2D) discontinuous map. We obtain stability conditions of the border and interior fixed points (known as Solow and Pasinetti equilibria, respectively) and investigate bifurcation structures observed in the parameter space of this map, associated with its attracting cycles and chaotic attractors. In particular, we show that on the x-axis, which is invariant, the map is reduced to a 1D piecewise increasing discontinuous map, and prove the existence of a corresponding period adding bifurcation structure issuing from a codimension-two border collision bifurcation point. Then, we describe how this structure evolves when the related attracting cycles on the x-axis lose their transverse stability via a transcritical bifurcation and the corresponding interior cycles appear. In particular, we show that the observed bifurcation structure, being associated with the 2D discontinuous map, is characterized by multistability, that is impossible in the case of a standard period adding bifurcation structure.

This chapter acquaints the reader with the use of dynamic models in regional economics. The focus is on the New Economic Geography (NEG) approach. A brief comparison is provided between NEG and other economic approaches to investigate regional inequalities. The analytic structure of a general multi-regional model is described, and some simple examples are presented, where the number of regions is assumed to be small to obtain more easily analytic and numerical results. Tools from the mathematical theory of dynamical systems are drawn to study the qualitative properties of such multi-regional model.