854 resultados para Mobile obstacle


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The Austrian government may have failed in its efforts in 2005 to have ‘privileged partnership' inserted into the European Union's framework for accession negotiations with Turkey, but this did not prevent the country's Chancellor, Wolfgang Schussel, from claiming that ‘for the first time ever, we have set an extra condition which will yet be very important in the future for Europe, namely the ability of the Union to take in new members'. Indeed, since its inclusion in the framework for negotiations, the EU's ‘capacity to absorb' new members is referred to as a new criterion for further enlargement of the European Union (EU). When opponents of Turkey 's membership, like Schussel, celebrate the emphasis on the EU's ‘absorption capacity', Turks generally regard it as specially-designed extra obstacle to their membership aspirations even if the EU's ‘absorption capacity' is a permanent agenda item whenever the EU discusses enlargement. This article explores the origins of this – supposedly new – condition and argues that the increased emphasis on the EU's ‘absorption capacity' can be explained by the shifts in the dynamics of EU enlargement.

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In many bird species with biparental care for young in the nest, hungry chicks beg repeatedly and parents adjust their feeding rate to the call rate of young. Repetitive calling also occurs in fledglings and in some mammals where offspring follow provisioners. It is not yet clear whether, in mobile systems with dispersed young where adults cannot compare the vocal behaviour of all young simultaneously, the calls represent a signal of need. We investigated repetitive begging by cooperatively reared meerkat, Suricata suricatta, pups that foraged with the group. Pups produced two types of begging calls: repeat calls over long periods and high-pitched calls mainly confined to feeding events. Food-deprived pups stayed closer to feeders, and begged for longer and more intensely by calling at a higher rate. Hungry pups increased both the rate of repeat calls, which were given continually, and the number of high-pitched bouts, but adults increased their food allocation only in relation to the rate of repeat calls. Our study indicates that hunger may lead to several changes in vocal behaviour, only some of which may be used by adults to assess need.

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A first-generation, mobile, video-based reminder system offers memory support to those afflicted with mild-stage Alzheimer's disease.

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This paper presents a new architecture together with practical results for a high performance analogue retrodirective array architecture with the following significant advantages: (1) It is able to constructively combine signals on receive, as well as on transmit, a feature not seen before on this type of array, (2) It is capable of operating with real life communication received signal levels as low as -120dBm. This work opens the way for fully co-operating Retrodirective arrays for use on un-stabilized co-operating mobile platforms where maximum S/N simultaneously on receive and on retransmit is automatically guaranteed.

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This paper presents a feature selection method for data classification, which combines a model-based variable selection technique and a fast two-stage subset selection algorithm. The relationship between a specified (and complete) set of candidate features and the class label is modelled using a non-linear full regression model which is linear-in-the-parameters. The performance of a sub-model measured by the sum of the squared-errors (SSE) is used to score the informativeness of the subset of features involved in the sub-model. The two-stage subset selection algorithm approaches a solution sub-model with the SSE being locally minimized. The features involved in the solution sub-model are selected as inputs to support vector machines (SVMs) for classification. The memory requirement of this algorithm is independent of the number of training patterns. This property makes this method suitable for applications executed in mobile devices where physical RAM memory is very limited. An application was developed for activity recognition, which implements the proposed feature selection algorithm and an SVM training procedure. Experiments are carried out with the application running on a PDA for human activity recognition using accelerometer data. A comparison with an information gain based feature selection method demonstrates the effectiveness and efficiency of the proposed algorithm.