169 research outputs found
Signification de la présence de pseudomonadacea dans des Yoghourts préparés en Algérie
No full textComby L., Tysset Camille, Crochemore . Signification de la présence de pseudomonadacea dans des Yoghourts préparés en Algérie. In: Bulletin de l'Académie Vétérinaire de France tome 115 n°2, 1962. pp. 59-65
On-line construction of a small automaton for a finite set of words
No full textIn this paper we describe a ``light'' algorithm for the on-line construction
of a small automaton recognising a finite set of words.
The algorithm runs in linear time.
We carried out good experimental results on the
suffixes of a text, showing how this automaton is small. For the
suffixes of a text, we propose a modified construction that leads
to an even smaller automaton
Towards a solution to the "Runs" conjecture
No full textThe "runs" conjecture, proposed by [Kolpakov and Kucherov, 1999], states that the number of occurrences of maximal repetitions (runs) in a string of length n is at most n. The best bound to date, due to [Crochemore and The, 2007], is 1.6n. Here we improve very much this bound using a combination of theory and computer verification. Our best bound is 1.048n but actually solving the conjecture seems to be now only a matter of tim
From seasonal forecast skill to end-user economic benefit: the case of the Lake Como
No full textRecent increase in spatiotemporal model resolution, availability of data/monitored variables, improvement in initialization procedures, and more accurate representation of physical processes contributed in advancing the quality of weather and climate services. State-of-the-art meteorological and hydrological forecast services are becoming more and more skillful over seasonal timescales, potentially representing an asset for informing strategic decisions in different economic sectors. Such services can play a key role in irrigated agriculture for supporting crop choices and irrigation scheduling decisions, which strongly depend on the expected hydro-meteorological conditions. However, although the accuracy and reliability of forecast services depend on the set up of the models that generate the forecasts, their (added) value also depends on how decision makers use the provided information in operational contexts.
In this work, we contribute a novel framework to assess the value of weather and climate services, by extending traditional forecast quality assessment methods with estimates of the potential end-user economic benefit from using forecast information. We also explore the sensitivity of the potential economic benefit on both the model set up and decision maker behavioral factors. The framework is demonstrated on the Lake Como system (Italy), a regulated lake primarily operated for flood protection and irrigation supply.
Our framework relies on the following integrated modeling chain: 1) lake inflows are produced from bias adjusted ECMWF System 4 seasonal forecasts used as input to the continentally-calibrated E-HYPE hydrological model; 2) this information is then used for conditioning the daily lake operations; 3) the resulting lake releases finally feed an agricultural model to estimate the net profit of the farmers in the downstream irrigation district. The whole chain was run for a 12-year period running from 1996 to 2007, including a fairly balanced number of normal, wet, and dry agricultural seasons.
Results suggest that, on average, informing the Lake Como operations based on ECMWF System 4 coupled with E-HYPE hydrological forecasts allows gaining about 4% of farmers’ profit with respect to a traditional operating policy conditioned on the modelled inflow climatology. This gain rises up to 16% during intense drought episodes. Moreover, this value is shown to be particularly sensitive to climate forcing inputs, but also on how the lake operator uses the forecast information depending on the different perceptions of risk and uncertaint
Isolating the Role of End-User Behavior in the Assessment of Seasonal Forecast Value
No full textRecent improvements in model resolutions, initialization procedures, and representation of large scale hydro-meteorological processes contributed in advancing the accuracy of hydroclimatic forecasts, which are more and more skillful over the seasonal and longer timescales. These forecasts are potentially valuable for informing multisector strategic decisions, including irrigated agriculture, where they can improve crop choices and irrigation scheduling decisions. In this operational context, forecast accuracy is important but not necessarily proportional to the associated economic marginal benefit, which is also affected by how forecasts are employed by end-users.
In this work, we contribute a novel framework to quantify the value of hydroclimatic forecasts by extending traditional quality assessments with estimates of the potential economic benefit of the forecasts to the end-user. We also explore the sensitivity of this benefit to both model set up and end-user behavioral factors. The approach is demonstrated on the Lake Como system (Italy), a regulated lake operated for flood protection and irrigation supply. Our framework relies on an integrated modeling chain composed of three building blocks: bias-adjusted seasonal meteorological forecasts are used as input to the continentally-calibrated E-HYPE hydrological model; predicted lake inflows are used for conditioning the daily lake operations; the resulting lake releases feed an agricultural model to estimate the net profit of the farmers in a downstream irrigation district.
Results suggest that, on average, informing the Lake Como operations based on E-HYPE hydrological forecasts allows gaining about 1% of the farmers’ profit with respect to a baseline solution not informed by any forecast. This gain rises up to about 15% during intense drought episodes. Moreover, our analysis suggests that this value can be largely attributed to the hydrological model and its initial conditions, while the role of meteorological forcing emerges only during dry seasons. Lastly, our results show a high sensitivity to behavioral factors capturing different perception of risk and uncertainty, with the estimated forecast value being potentially undermined if end-users are not able to properly extract the most valuable information from the forecast ensemble
From skill to value: Isolating the influence of end user behavior on seasonal forecast assessment
No full textRecent improvements in initialization procedures and representation of large-scale hydrometeorological processes have contributed to advancing the accuracy of hydroclimatic forecasts, which are progressively more skillful over seasonal and longer timescales. These forecasts are potentially valuable for informing strategic multisector decisions, including irrigated agriculture, for which they can improve crop choices and irrigation scheduling. In this operational context, the accuracy associated with the forecast system setup does not necessarily yield proportional marginal benefit, as this is also affected by how forecasts are employed by end users. This paper aims at quantifying the value of hydroclimatic forecasts in terms of potential economic benefit to the end users, which allows for the inference of a relation between gains in forecast skill and gains in end user profit. We also explore the sensitivity of this benefit to both forecast system setup and end user behavioral factors. These analyses are supported by an evaluation framework demonstrated on the Lake Como system (Italy), a regulated lake operated for flood protection and irrigation supply. Our framework relies on an integrated modeling chain composed of three building blocks: bias-adjusted seasonal meteorological forecasts are used as input to the continentally calibrated E-HYPE hydrological model; predicted lake inflows are used for conditioning the daily lake operations; and the resulting lake releases feed an agricultural model to estimate the net profit of the farmers in a downstream irrigation district. Results suggest that despite the gain in average conditions being negligible, informing the operations of Lake Como based on seasonal hydrological forecasts during intense drought episodes allows about 15 % of the farmers' profit to be gained with respect to a baseline solution not informed by any forecast. Moreover, our analysis suggests that behavioral factors capturing different perceptions of risk and uncertainty significantly impact the quantification of the benefit to the end users, whereby the estimated forecast value is potentially undermined by different levels of end user risk aversion. Lastly, our results show an intricate skill-to-value relation modulated by the underlying hydrologic conditions, which is well aligned over an exponential function in dry years, while the gains in profit are almost insensitive to the improvements in forecast skill in wet years
Finding Maximal Pairs with Bounded Gap
No full textBrodal GS, Lyngsø RB, Pedersen CNS, Stoye J. Finding Maximal Pairs with Bounded Gap. In: Crochemore M, Gąsieniec L, eds. Matching Patterns (Journal of Discrete Algorithms). 2000: 77-104
Pathways to designing and running an operational flood forecasting system: an adventure game!
No full textIn the design and building of an operational flood forecasting system, a large number of decisions have to be taken. These include technical decisions related to the choice of the meteorological forecasts to be used as input to the hydrological model, the choice of the hydrological model itself (its structure and parameters), the selection of a data assimilation procedure to run in real-time, the use (or not) of a post-processor, and the computing environment to run the models and display the outputs. Additionally, a number of trans-disciplinary decisions are also involved in the process, such as the way the needs of the users will be considered in the modelling setup and how the forecasts (and their quality) will be efficiently communicated to ensure usefulness and build confidence in the forecasting system. We propose to reflect on the numerous, alternative pathways to designing and running an operational flood forecasting system through an adventure game. In this game, the player is the protagonist of an interactive story driven by challenges, exploration and problem-solving. For this presentation, you will have a chance to play this game, acting as the leader of a forecasting team at an operational centre. Your role is to manage the actions of your team and make sequential decisions that impact the design and running of the system in preparation to and during a flood event, and that deal with the consequences of the forecasts issued. Your actions are evaluated by how much they cost you in time, money and credibility. Your aim is to take decisions that will ultimately lead to a good balance between time and money spent, while keeping your credibility high over the whole process. This game was designed to highlight the complexities behind decision-making in an operational forecasting and emergency response context, in terms of the variety of pathways that can be selected as well as the timescale, cost and timing of effective actions
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