1,246 research outputs found

    The Acoustics of Social Learning: Designing learning processes that contribute to a more sustainable world.

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    Learning for Sustainable Development contributes to a society in which citizens, companies, organisations, and authorities learn about sustainable development and are desiring, willing, and able to contribute to it

    Pricing in the hotel and catering sector

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    A model explaining gross margins in the hotel and catering sector is developed. A cost-mark-up model for the retail sector is used as a starting point. Although we have to reject the hypothesis of mark-up pricing in the hotel and catering sector, the model proves a useful instrument to discriminate between such influences as sales composition, costs and their various components, scale and demand conditions on price setting. Our empirical evidence stems from the Dutch hotel and catering sector (1977 through 1981)

    Trading-off payments and accuracy in online classification with paid stochastic experts

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    We investigate online classification with paid stochastic experts. Here, before making their prediction, each expert must be paid. The amount that we pay each expert directly influences the accuracy of their prediction through some unknown Lipschitz “productivity” function. In each round, the learner must decide how much to pay each expert and then make a prediction. They incur a cost equal to a weighted sum of the prediction error and upfront payments for all experts. We introduce an online learning algorithm whose total cost after T rounds exceeds that of a predictor which knows the productivity of all experts in advance by at most O(K2(lnT)T−−√) where K is the number of experts. In order to achieve this result, we combine Lipschitz bandits and online classification with surrogate losses. These tools allow us to improve upon the bound of order T2/3 one would obtain in the standard Lipschitz bandit setting. Our algorithm is empirically evaluated on synthetic data

    Intensive care unit depth of sleep:proof of concept of a simple electroencephalography index in the non-sedated

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    INTRODUCTION: Intensive care unit (ICU) patients are known to experience severely disturbed sleep, with possible detrimental effects on short- and long- term outcomes. Investigation into the exact causes and effects of disturbed sleep has been hampered by cumbersome and time consuming methods of measuring and staging sleep. We introduce a novel method for ICU depth of sleep analysis, the ICU depth of sleep index (IDOS index), using single channel electroencephalography (EEG) and apply it to outpatient recordings. A proof of concept is shown in non-sedated ICU patients. METHODS: Polysomnographic (PSG) recordings of five ICU patients and 15 healthy outpatients were analyzed using the IDOS index, based on the ratio between gamma and delta band power. Manual selection of thresholds was used to classify data as either wake, sleep or slow wave sleep (SWS). This classification was compared to visual sleep scoring by Rechtschaffen & Kales criteria in normal outpatient recordings and ICU recordings to illustrate face validity of the IDOS index. RESULTS: When reduced to two or three classes, the scoring of sleep by IDOS index and manual scoring show high agreement for normal sleep recordings. The obtained overall agreements, as quantified by the kappa coefficient, were 0.84 for sleep/wake classification and 0.82 for classification into three classes (wake, non-SWS and SWS). Sensitivity and specificity were highest for the wake state (93% and 93%, respectively) and lowest for SWS (82% and 76%, respectively). For ICU recordings, agreement was similar to agreement between visual scorers previously reported in literature. CONCLUSIONS: Besides the most satisfying visual resemblance with manually scored normal PSG recordings, the established face-validity of the IDOS index as an estimator of depth of sleep was excellent. This technique enables real-time, automated, single channel visualization of depth of sleep, facilitating the monitoring of sleep in the ICU
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