In this study Active Learning Method (ALM) as a novel fuzzy modeling approach is compared with optimized Support Vector Machine (SVM) using simple Genetic Algorithm (GA), as a well known datadriven model for long term simulation of daily streamflow in Karoon River. The daily discharge data from 1991 to 1996 and from 1996 to 1999 were utilized for training and testing of the models, respectively. Values of the Nash-Sutcliffe, Bias, R2 , MPAE and PTVE of ALM model with 16 fuzzy rules were 0.81, 5.5 m3 s -1, 0.81, 12.9%, and 1.9%, respectively. Following the same order of parameters, these criteria for optimized SVM model were 0.8, -10.7 m3 s-1, 0.81, 7.3%, and -3.6%, respectively. The results show appropriate and acceptable simulation by ALM and optimized SVM. Optimized SVM is a well-known method for runoff simulation and its capabilities have been demonstrated. Therefore, the similarity between ALM and optimized SVM results imply the ability of ALM for runoff modeling. In addition, ALM training is easier and more straightforward than the training of many other data driven models such as optimized SVM and it is able to identify and rank the effective input variables for the runoff modeling. According to the results of ALM simulation and its abilities and properties, it has merit to be introduced as a new modeling method for the runoff modeling. and Cieľom štúdie bolo porovnať možnosti dlhodobej simulácie denných prietokov v rieke Karoon pomocou novovyvinutej fuzzy metódy aktívneho učenia (Active Learning Method - ALM) a známej metódy vektormi podporených strojov (Support Vector Machine - SVM), optimalizovanej genetickým algoritmom (GA). Na tréning a testovanie modelov boli použité časové rady denných prietokov za obdobie rokov 1991 až 1996 a 1996 až 1999. Hodnoty parametrov Nash-Sutcliffe, Bias, R2 , MPAE a PTVE pre model ALM boli 0,81; 5,5 m3 s-1; 0,81; 12,9% a 1,9%. Parametre v tom istom poradí pre model SVM boli 0,8 -10,7 m3 s-1, 0,81; 7,3%; a -3,6%. Z výsledkov simulácií vyplýva, že aplikáciou metód ALM a SVM možno získať porovnateľné a akceptovateľné výsledky. Podobnosť výsledkov medzi ALM a SVM implikuje vhodnosť novovyvinutej metódy ALM pre simuláciu odtoku. Tréning ALM je ľahší a jednoduchší ako je tréning ďalších dátami riadených modelov podobného typu. Navyše algoritmus ALM je schopný identifikovať a zoradiť efektívne vstupné premenné pre modelovanie odtoku. Na základe dosiahnutých výsledkov možno metódu ALM zaradiť medzi nové, alternatívne metódy modelovania odtoku.
The changed socio-political conditions and transformation processes after 1989 had a significant impact on many spheres of life of our society. The text discusses these circumstances in connection with the issue of breastfeeding and its reflection from the perspective of mothers of two generations. The rise in popularity of breastfeeding and its preferences as the most appropriate method of nutrition in young children has been apparent for longer than adecade not only in Slovakia. This has been confirmed by works in the medical field as well as research on a specific sample of informants, on which the study is based. It attempts to reach an ethnological interpretation of the perception of breastfeeding by current mothers and women of an older generation. It confronts the attitudes of older women and current mothers towards breastfeeding and phenomena related thereto. It concludes that in recent years breastfeeding has been on the rise in comparison with the previous generation of mothers. The author considers the increased promotion of breastfeeding and the irreplaceability of breast milk in child nutrition to be the main factors contributing to this situation.