311. Mapping and conservation of dry grasslands on the edge of Mediterranean basinMitja Kaligarič, Branka Trčak, Bojana Lipej, Andrej Sovinc, 2004, published professional conference contribution Abstract: Among conservation efforts regarding man-made ecosystems, conservation of dry grasslands on the edge of the Mediterranean basin, represent one of the most difficult challenges. These grasslands, namely, do not suffer so much the desertification, but spontaneous afforestation after abandonment. On the area Kraški rob within the North Adriatic karst, 70 km2 ha has been mapped according to PHYSIS typology. The 15.68 % of the total surface represents grasslands without visible afforestation. But completely changed socio-economic trends in the area (abandonment of agriculture) make keeping the valuable grasslands in good conditions very difficult. An alternative solution was found through activities of the LIFE - Nature project. Mowing and transporting more than 65 tons of hay from the research area to the Lipica stud farm were organized in year 2004 with management prescriptions and plan to arrange a long-term agreement with beneficial effect to grassland biodiversity.
Keywords: ekologija, botanika, varstvo narave, Kraški rob, habitati, kartiranje
Published in RUP: 15.10.2013; Views: 4080; Downloads: 49
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319. Machine learning helps physicians in diagnosing of mitral valve prolapsePetra Povalej Bržan, Mitja Lenič, Milan Zorman, Peter Kokol, Lenka Lhotska, Rado Pišot, 2003, original scientific article Abstract: In this paper we present a multimethod approach for induction of a specific class of classifiers, which can assist physicians in medical diagnosing in the case of mitral valve prolapse. Mitral valve prolapse is one of the most controversial prevalent cardiac condition and may affect up to ten percent of the population and in the worst case results in sudden death. MultiVeDec is a general framework enabling researchers to generate various intelligent tools based on machine learning. In this paper we focused on various decision tree methods, which are capable of extracting knowledge in a form closer to human perception, a feature that is very important in medical field. The experiment included classifiers with various classical single method approaches, evolutionary approaches, hybrid approaches and also our newest multimethod approach. The main concern of the latest approach is to find a way to enable dynamic combination of methodologies to the somehow quasi unified knowledge representation. The proposed multimethod approach was capable to outperform all other tested approaches by producing classifier for diagnosing mitral valve prolapse with the highest overall and average class accuracy. More importantly, it was also capable to find some new knowledge important in diagnosing of mitral valve prolapse.
Published in RUP: 15.10.2013; Views: 3337; Downloads: 39
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