Basics of inventory management (Part 4: The (s,S)-model)

Inventory Models;management science

Basics of inventory management (Part 6: The (R,s,S)-model)

Inventory Models;management science

Basics of inventory management (Part 5: The (R,b,Q)-model)

Inventory Models;management science

Analyzing Nonverbal Listener Responses using Parallel Recordings of Multiple Listeners

In this paper we study nonverbal listener responses on a corpus with multiple parallel recorded listeners. These listeners were meant to believe that they were the sole listener, while in fact there were three persons listening to the same speaker. The speaker could only see one of the listeners. We analyze the impact of the particular setup of the corpus on the behavior and perception of the two types of listeners; the listeners that could be seen by the speaker and the listeners that could not be seen. Furthermore we compare the nonverbal listening behaviors of these three listeners to each other with regard to timing and form. We correlate these behaviors with behaviors of the speaker, like pauses and whether the speaker is looking at the listeners or not

On the Noncommutativity Approach to Supersymmetry on the Lattice

The noncommutativity approach to SUSY on the lattice is shown to be inconsistent and a similar inconsistency is displayed for the link approach.Comment: 3 pages; talk presented by FB at "Quark Confinement and the Hadron Spectrum VII", September 2-7, 2006, Ponta Delgada, Azores, Portuga

Living With Peak Discharge Uncertainty: The Self-learning Dike

Although river dikes still play a key role for flood protection in the Netherlands\ud there is a growing interest for other measures to deal with larger peak discharges, such as\ud lowering or widening the floodplains. Regardless of the strategy chosen the assessment of\ud its effect on the flood risk depends on the peak discharge statistics. A problem here is that\ud the statistical analysis of peak discharges relies on probability distributions based on the\ud limited time series of extreme discharges. The extrapolation of these distributions are\ud subject to considerable uncertainty, because there is a measuring record of only about 100\ud years and the natural variability can be expected to change as a result of climate change.\ud This raises the question whether a more direct response to the effects of climate change is\ud possible. The natural variability of the peak discharge changes, the changes in this\ud variability due to e.g. climate change and the new statistical distribution can only be\ud established after the actual change has happened. Even with regular updates of the\ud statistical distributions it is inherent that the actions taken to reduce the flood risk are not\ud anticipatory but delayed. As an alternative, this paper presents an adaptive or so-called selflearning\ud approach to deal with the uncertainty in the peak discharge statistics. The\ud difference with the probabilistic design of flood defense works, which depends on the\ud analysis and prediction of uncertain peak discharges, is that the dike is adapted in direct\ud response to peak water levels exceeding the dike height minus a certain safety margin. The\ud results indicate that, on average, adaptive flood management based on observed peak water\ud levels is at least as safe as a probabilistic approach, which necessarily relies on uncertain\ud discharge statistics. Other advantages of the adaptive strategy are also obvious: the rule of\ud response is simple and easy to communicate to the public, and peak water levels are less\ud difficult to measure. In general the example demonstrates that flood management can be\ud based on a direct response to the effects of climate change, without tedious statistical\ud analysis of peak discharge records

Adapting to climate change: the self-learning dike

A problem with the current probabilistic flood prevention strategy in the Netherlands is that it builds on knowledge about the probability distributions for extreme discharges, which are subject to considerable uncertainties due to limited peak discharge records and climate change. It is inherent to this strategy that the actions taken to reduce the flood risk are not anticipatory but following. In the historic flood prevention strategy (practised until the 1950s), referred to as the ‘self-learning dike’, the dike height is kept at a level equal to the highest recorded water level in history plus a certain\ud safety margin. The two flood-prevention strategies are compared on the basis of the average flooding safety during a 100-year period, with the Rhine River at Lobith taken as case example. The results indicate that the self-learning dike performs as well, even slightly better, as the probabilistic design in terms of safety and reasonably in terms of the size and number of adaptations of the dike height, even under climate change

A Survey on Evaluation Metrics for Backchannel Prediction Models

In this paper we give an overview of the evaluation metrics used to measure the performance of backchannel prediction models. Both objective and subjective evaluation metrics are discussed. The survey shows that almost every backchannel prediction model is evaluated with a different evaluation metric. This makes comparison between developed models unreliable, even beside the other variables in play, such as different corpora, language, conversational setting, amount of data and/or definition of the term backchannel

Do Small Businesses Create More Jobs? New Evidence for Europe

In this paper we argue why, in our view, the so-called dynamic classification method should be favored when determining the contribution of small businesses towards job creation. First, it is the only method that consistently attributes job creation or loss to the size class in which it actually occurs. In addition, dynamic classification has two other advantages: (i) it is not vulnerable to the so-called regression to the mean bias and (ii) only a small number of aggregated data are required for its application. Using the dynamic classification we analyze job creation within the different size classes for the 27 Member States of the European Union. Our main findings are as follows: For the EU as a whole, smaller firms contribute on a larger scale towards job creation than larger firms do. Net job creation rates decrease with each firm size class. This pattern occurs in most industries however, not in all: the manufacturing industry and trade industry show different patterns. At the level of individual countries, the net job creation rate also tends todecrease with each firm size class. However, this relation is not perfect.