Variations of the renal flow in relation with the volemia.
Philippe ArbeilleD. LebouardF. PatatJ M PottierJay C. BuckeyLuis BeckGöran BlomqvistC GharibL. Pourcelot
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Online traffic flow modeling is attracting more attention due to intelligent transport systems and technologies. The flow-density relation plays an important role in traffic flow modeling and provides a basic way to illustrate traffic flow behavior under different traffic flow and traffic density conditions. Until now the research effort has focused mainly on identifying the shape of the relation. The time-traced plot of the relation has not been identified and utilized properly even though the time-traced plot of the relation reflects the upstream/downstream traffic conditions and should be considered in the traffic flow modeling. In this paper the flow-density relation is analyzed considering the time-development of the relation and interpreted as a states diagram. The time-traced plot of the flow-density relation is quantified by applying fuzzy logic. The quantified time-traced plot of the flow-density relation builds the basis for online application of a macroscopic traffic flow model. The new approach to online modeling of traffic flow applying the time-traced plot of the flow-density relation alleviates parameter calibration problems stemming from the flow-density relation.
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Labor service relation, employment relation and labor relation are three correlated but different concepts. In academic circles and real practices, there are different perceptions of and views on the relationships among them. By analyzing the differences and similarities of these three concepts, we find that the relation between labor service relation and employment relation is parallel relation and the relation between employment relation and labor relation is subordinate relation. Constructing reasonable relationship structure of these three relations could not only be beneficial to clearly discern the differences among the three relations, but also be good for reasonably establishing and utilizing the legal system, whose function is to adjust the relationships among the three relations.
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Online traffic flow modeling is attracting more attention due to intelligent transport systems and technologies. The flow-density relation plays an important role in traffic flow modeling and provides a basic way to illustrate traffic flow behavior under different traffic flow and traffic density conditions. Until now the research effort has focused mainly on the shape of the relation. The time series of the relation has not been identified clearly, even though the time series of the relation reflects the upstream/downstream traffic conditions and should be considered in the traffic flow modeling. In this paper the flow-density relation is analyzed dynamically and interpreted as a states diagram. The dynamic flow-density relation is quantified by applying fuzzy logic. The quantified dynamic flow-density relation builds the basis for online application of a macroscopic traffic flow model. The new approach to online modeling of traffic flow applying the dynamic flow-density relation alleviates parameter calibration problems stemming from the static flow-density relation.
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Abstract Online traffic flow modeling is of increasing importance due to intelligent transport systems and technologies. The flow-density relation plays an important role in traffic flow modeling and provides a basic way to illustrate traffic flow behavior under different traffic flow and traffic density conditions. Until now the research effort has focused mainly on the shape of the relation. The time series of the relation has not been identified clearly, even though the time series of the relation reflects the upstream/downstream traffic conditions and should be considered in the traffic flow modeling. In this paper, the dynamic flow-density relation is identified based on the classification of traffic states and is quantified employing fuzzy logic. The quantified dynamic flow-density relation builds the basis for online application of a macroscopic traffic flow model. The new approach to online modeling of traffic flow applying the dynamic flow-density relation alleviates parameter calibration problems stemming from the static flow-density relation.
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