Fluid Modelling: A Step Toward More Adequate Modelling
One of the main problems at modelling economic systems is changing of the structure of the system. It is especialy important for economic situation in Yugoslavia during last few years. It’s characteristic is drastic changing of inner relationships as a consequence of the proposed economic reform and hyperinflation trends. This means that the structure of the existing economic system is changing (the structure between main macroeconimic sectors). When the a priori informations about model are unknown, an adaptive model is needed. Adaptability means that it is possible to: (1) change the values of parameters; (2) change the structure of the model so that it corresponds to the changes of the structure of the system under control; (3) modify goals and criterions according to the additional informations about surroundings; (4) change limitations control actions due to changes of available resources. The subject of researches in this work is the “structural adaptability” that is models with unknown input-output mapping operator.
Some experiences with fluid modeling of economic systems
This paper deals with a new approach to modeling of economic systems, called fluid modeling. The main feature of this approach amounts to a revised concept of dynamics. After having established a set of requirements towards economic modeling we represent a practical example on fluid dynamic modeling of a particular macroeconomic system and discuss the extent to which the basic requirements of fluid modeling have been fulfilled.
An automated retinal image quality grading algorithm
This paper introduces an algorithm for the automated assessment of retinal fundus image quality grade. Retinal image quality grading assesses whether the quality of the image is sufficient to allow diagnostic procedures to be applied. Automated quality analysis is an important preprocessing step in algorithmic diagnosis, as it is necessary to ensure that images are sufficiently clear to allow pathologies to be visible. The algorithm is based on standard recommendations for quality analysis by human screeners, examining the clarity of retinal vessels within the macula region. An evaluation against a reference standard data-set is given; it is shown that the algorithm's performance correlates closely with that of clinicians manually grading image quality.