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Artificial intelligence --- Fuzzy sets --- Rough sets --- Decision Making --- Uncertainty --- Mathematical models --- Artificial intelligence. --- Decision making --- Fuzzy sets. --- Rough sets. --- Uncertainty. --- Mathematical models. --- Decision Making - Mathematical models

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Image processing. --- Pattern perception. --- Soft computing.

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Observations on the agonistic behaviour of 12 free-ranging dogs from two neighbouring groups were recorded in Katwa town, India. Both intra- and inter-group agonistic encounters were recorded on a seasonal basis. Mean (+/- S.E.) seasonal number of intra-group agonistic encounters of individual dog was greatest in winter (13.33 +/- 1.89) and then in late monsoon (12.33 +/- 1.99), when the females were lactating and in oestrus, respectively. Similarly, the mean (+/-S.E.) seasonal number of inter-group agonistic encounters of individual dog was greatest in winter (32.25 +/- 4.43) and then in late monsoon (27.75 +/- 2.01). There was a significant difference between the intra- and inter-group agonistic encounters. Dominance hierarchies were established among the adult dogs of either sex based on aggressive encounters. Although individual differences in agonism were observed, overall levels of aggression were higher among the adult females than for other groups. In contrast, overall levels of submission were higher among the juvenile males than for other groups. The results from this study suggest that reproductive season, sex and age have a significant effect on the agonistic behaviour of free-ranging dogs. (C) 1998 Elsevier Science B.V. All rights reserved

Adult. --- Age. --- Aggression. --- Aggressive. --- Agonistic behaviour. --- Agonistic. --- Behaviour. --- Canis-familiaris. --- Canis. --- Dispersal. --- Dog,agonistic behaviour,aggression,submission,courting,seasonal dynamics,sex influence,age influence. --- Dog. --- Dogs. --- Dominance hierarchies. --- Dominance. --- Female. --- Females. --- Group. --- Hierarchy. --- Individual difference. --- Individual differences. --- Individual-differences. --- Level. --- Male. --- Males. --- Observation. --- Oestrus. --- Population. --- Red foxes. --- Season. --- Sex. --- Sexes. --- Social-organization. --- Submission. --- Territory maintenance. --- Urban dogs. --- Wolves.

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The 8th International Workshop on Fuzzy Logic and Applications (WILF 2009) held in Palermo (Italy), June 9-12, 2009, covered topics related to theoretical and experimental areas of fuzzy sets and systems with emphasis on di?erent applications. This eventrepresentsthe continuation ofan established traditionof biannual interdisciplinary meetings. The previous editions of WILF were held, with an increasing number of participants, in Naples (1995), Bari (1997), Genoa (1999), Milan (2001), Naples (2003), Crema (2005) and Camogli (2007). Each event focused on distinct main thematic areas of fuzzy logic and related applications. WILF 2009 aimed to highlight connections and synergiesof fuzzy sets theory with nonconventional computing (e.g., neural networks, evolutionary compu- tion, support vector machines, molecular computing, quantum computing) and cognitivescience,inordertoreachabetterunderstandingofbothnaturaland- ti?cial complex systems as well as computing systems, inspired by nature, which are able to solve complex problems. From this perspective one of the main goals of the WILF workshops is to bring together researchers and developers from both academia and high-tech companies. WILF 2009receivedmorethan 60 paper submissionsfrom all overthe world, including Algeria, Belgium, Benin, Brazil, Canada, China, France, Greece, India, Iran, Italy, Japan, Poland, Romania, Slovakia, Spain and the USA. A rigorous peer-review selection process was applied to ultimately select nearly 40 high-quality manuscripts to be published in this volume. Moreover,thevolumealsoincludespresentationsfromthreekeynotespeakers EtienneKerre(GhentUniversity,Belgium),SankarK.Pal(ISI,India)andEnric Trillas (ECSC, Spain).

Mathematical logic --- Mathematical statistics --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- beeldverwerking --- IR (information retrieval) --- factoranalyse --- informatica --- wiskunde --- KI (kunstmatige intelligentie) --- logica --- robots

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Soft computing comprises various paradigms dedicated to approximately solving real-world problems, e.g., in decision making, classification or learning; among these paradigms are fuzzy sets, rough sets, neural networks, and genetic algorithms. It is well understood now in the soft computing community that hybrid approaches combining various paradigms provide very promising attempts to solving complex problems. Exploiting the potential and strength of both neural networks and rough sets, this book is devoted to rough-neurocomputing which is also related to the novel aspect of computing based on information granulation, in particular to computing with words. It provides foundational and methodological issues as well as applications in various fields.

Natural language processing (Computer science). --- Neural computers. --- Rough sets. --- Soft computing.