In this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones – the healthy blood cells (erythrocytes) and the pathologic ones (echinocytes). The separated blood cells are analysed in terms of their most important features by the eigenfaces method. The features are the basis for designing the neural network classifier, learned to distinguish between erythrocytes and echinocytes. As the result, the proposed system is able to analyse the smear blood images in a fully automatic way and to deliver information on the number and statistics of the red blood cells, both healthy and pathologic. The system was examined in two case studies, involving the canine and human blood, and then consulted with the experienced medicine specialists. The accuracy of classification of red blood cells into erythrocytes and echinocytes reaches 96%.
The main objective of the article is an attempt to indicate factors which determine the image of a city as a good place to live as well as to reveal the ways in which they affect the citizens’ quality of life. In order to do so, the author selected the city of Gdynia which is perceived as the best city to live in by its citizens. Among the most important factors determining the quality of life in general there are: the scale of a city, local identity, public spaces, symbolic places, housing environment, perception of a place, personal satisfaction of a place where a particular person lives, urban policies as well as presence and activeness of local leaders. The article presents the results of a social study carried out by the author herself during two periods of time – in 2004 and 2014 as well as the results of the Social Diagnosis 2015.