29,186 research outputs found
Iris Codes Classification Using Discriminant and Witness Directions
The main topic discussed in this paper is how to use intelligence for
biometric decision defuzzification. A neural training model is proposed and
tested here as a possible solution for dealing with natural fuzzification that
appears between the intra- and inter-class distribution of scores computed
during iris recognition tests. It is shown here that the use of proposed neural
network support leads to an improvement in the artificial perception of the
separation between the intra- and inter-class score distributions by moving
them away from each other.Comment: 6 pages, 5 figures, Proc. 5th IEEE Int. Symp. on Computational
Intelligence and Intelligent Informatics (Floriana, Malta, September 15-17),
ISBN: 978-1-4577-1861-8 (electronic), 978-1-4577-1860-1 (print
Cooperative Games with Overlapping Coalitions
In the usual models of cooperative game theory, the outcome of a coalition
formation process is either the grand coalition or a coalition structure that
consists of disjoint coalitions. However, in many domains where coalitions are
associated with tasks, an agent may be involved in executing more than one
task, and thus may distribute his resources among several coalitions. To tackle
such scenarios, we introduce a model for cooperative games with overlapping
coalitions--or overlapping coalition formation (OCF) games. We then explore the
issue of stability in this setting. In particular, we introduce a notion of the
core, which generalizes the corresponding notion in the traditional
(non-overlapping) scenario. Then, under some quite general conditions, we
characterize the elements of the core, and show that any element of the core
maximizes the social welfare. We also introduce a concept of balancedness for
overlapping coalitional games, and use it to characterize coalition structures
that can be extended to elements of the core. Finally, we generalize the notion
of convexity to our setting, and show that under some natural assumptions
convex games have a non-empty core. Moreover, we introduce two alternative
notions of stability in OCF that allow a wider range of deviations, and explore
the relationships among the corresponding definitions of the core, as well as
the classic (non-overlapping) core and the Aubin core. We illustrate the
general properties of the three cores, and also study them from a computational
perspective, thus obtaining additional insights into their fundamental
structure
Performance Evaluation of Road Traffic Control Using a Fuzzy Cellular Model
In this paper a method is proposed for performance evaluation of road traffic
control systems. The method is designed to be implemented in an on-line
simulation environment, which enables optimisation of adaptive traffic control
strategies. Performance measures are computed using a fuzzy cellular traffic
model, formulated as a hybrid system combining cellular automata and fuzzy
calculus. Experimental results show that the introduced method allows the
performance to be evaluated using imprecise traffic measurements. Moreover, the
fuzzy definitions of performance measures are convenient for uncertainty
determination in traffic control decisions.Comment: The final publication is available at http://www.springerlink.co
Diagnosis and decision-making for awareness during general anaesthesia
This is the post-print version of the article. The official published version can be obtained from the link below.We describe the design process of a diagnostic system for monitoring the anaesthetic state of patients during surgical interventions under general anaesthesia. Mid-latency auditory evoked potentials (MLAEPs) obtained during general anaesthesia are used to design a neuro-fuzzy system for the determination of the level of unconsciousness after feature extraction using multiresolution wavelet analysis (MRWA). The neuro-fuzzy system proves to be a useful tool in eliciting knowledge for the fuzzy system: the anaesthetist's expertise is indirectly coded in the knowledge rule-base through the learning process with the training data. The anaesthetic depth of the patient, as deduced by the anaesthetist from the clinical signs and other haemodynamic variables, noted down during surgery, is subsequently used to label the MLAEP data accordingly. This anaesthetist-labelled data, used to train the neuro-fuzzy system, is able to produce a classifier that successfully interprets unseen data recorded from other patients. This system is not limited, however, to the combination of drugs used here. Indeed, the similar effects of inhalational and analgesic anaesthetic drugs on the MLAEPs demonstrate that the system could potentially be used for any anaesthetic and analgesic drug combination. We also suggest the use of a closed-loop architecture that would automatically provide the drug profile necessary to maintain the patient at a safe level of sedation
Semantic distillation: a method for clustering objects by their contextual specificity
Techniques for data-mining, latent semantic analysis, contextual search of
databases, etc. have long ago been developed by computer scientists working on
information retrieval (IR). Experimental scientists, from all disciplines,
having to analyse large collections of raw experimental data (astronomical,
physical, biological, etc.) have developed powerful methods for their
statistical analysis and for clustering, categorising, and classifying objects.
Finally, physicists have developed a theory of quantum measurement, unifying
the logical, algebraic, and probabilistic aspects of queries into a single
formalism. The purpose of this paper is twofold: first to show that when
formulated at an abstract level, problems from IR, from statistical data
analysis, and from physical measurement theories are very similar and hence can
profitably be cross-fertilised, and, secondly, to propose a novel method of
fuzzy hierarchical clustering, termed \textit{semantic distillation} --
strongly inspired from the theory of quantum measurement --, we developed to
analyse raw data coming from various types of experiments on DNA arrays. We
illustrate the method by analysing DNA arrays experiments and clustering the
genes of the array according to their specificity.Comment: Accepted for publication in Studies in Computational Intelligence,
Springer-Verla
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