964 resultados para drivers scheduling problem


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Resulta sorprendente que un estudio pionero en Inglaterra sobre la pederastia griega como el de John Addington Symonds no cite el Erótico de Plutarco, excepción hecha de en algunas notas a pie de página, siendo como es este dialogo una seria reflexión filosófica sobre el eros griego, en que a menudo se abordan cuestiones éticas. El objetivo de este artículo es revelar justamente las razones de índole diversa para una tal omisión.

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Resulta sorprenent que un estudi pioner a Anglaterra sobre la pederàstia grega como el de John Addington Symonds no citi l'Eròtic de Plutarc, llevat de en algunes notes a peu de pàgina, essent com és aquest diàleg una seriosa reflexió filosòfica sobre l'eros grec, en què sovint s'aborden qüestions ètiques. L'objectiu d'aquest article és revelar justament les raons d'índole diversa per a una tal omissió.

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This paper applies probability and decision theory in the graphical interface of an influence diagram to study the formal requirements of rationality which justify the individualization of a person found through a database search. The decision-theoretic part of the analysis studies the parameters that a rational decision maker would use to individualize the selected person. The modeling part (in the form of an influence diagram) clarifies the relationships between this decision and the ingredients that make up the database search problem, i.e., the results of the database search and the different pairs of propositions describing whether an individual is at the source of the crime stain. These analyses evaluate the desirability associated with the decision of 'individualizing' (and 'not individualizing'). They point out that this decision is a function of (i) the probability that the individual in question is, in fact, at the source of the crime stain (i.e., the state of nature), and (ii) the decision maker's preferences among the possible consequences of the decision (i.e., the decision maker's loss function). We discuss the relevance and argumentative implications of these insights with respect to recent comments in specialized literature, which suggest points of view that are opposed to the results of our study.

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This brochure explains Iowa's laws that directly effect teenage drivers, their consequences and issues.

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We obtain the exact analytical expression, up to a quadrature, for the mean exit time, T(x,v), of a free inertial process driven by Gaussian white noise from a region (0,L) in space. We obtain a completely explicit expression for T(x,0) and discuss the dependence of T(x,v) as a function of the size L of the region. We develop a new method that may be used to solve other exit time problems.

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Report on a review of selected application controls over the Iowa Department of Transportation’s Driver’s License System for the period May 2, 2011 through May 27, 2011

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In a recent paper [Phys. Rev. Lett. 75, 189 (1995)] we have presented the exact analytical expression for the mean exit time, T(x,v), of a free inertial process driven by Gaussian white noise out of a region (0,L) in space. In this paper we give a detailed account of the method employed and present results on asymptotic properties and averages of T(x,v).

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In the Hamiltonian formulation of predictive relativistic systems, the canonical coordinates cannot be the physical positions. The relation between them is given by the individuality differential equations. However, due to the arbitrariness in the choice of Cauchy data, there is a wide family of solutions for these equations. In general, those solutions do not satisfy the condition of constancy of velocities moduli, and therefore we have to reparametrize the world lines into the proper time. We derive here a condition on the Cauchy data for the individuality equations which ensures the constancy of the velocities moduli and makes the reparametrization unnecessary.

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Coevolution is among the main forces shaping the biodiversity on Earth. In Eurasia, one of the best-known plant-insect interactions showing highly coevolved features involves the fly genus Chiastocheta and its host-plant Trollius. Although this system has been widely studied from an ecological point of view, the phylogenetic relationships and biogeographic history of the flies have remained little investigated. In this integrative study, we aim to test the monophyly of the five Chiastocheta eco-morphological groups, defined by Pellmyr in 1992, by inferring a mitochondrial phylogeny. We further apply a new approach to assess the effect of (i) different molecular substitution rates and (ii) phylogenetic uncertainty on the inference of the spatio-temporal evolution of the group. From a taxonomic point of view, we demonstrate that only two of Pellmyr's groups (rotundiventris and dentifera) are phylogenetically supported, the other species appearing para- or polyphyletic. We also identify the position of C. lophota, which was not included in previous surveys. From a spatio-temporal perspective, we show that the genus arose during the Pliocene in Europe. Our results also indicate that at least four large-scale dispersal events are required to explain the current distribution of Chiastocheta. Moreover, each dispersal to or from Asia is associated with a host-shift and seems to correspond to an increase in speciation rates. Finally, we highlight the correlation between diversification and climatic fluctuations, which indicate that the cycles of global cooling over the last million years had an influence on the radiation of the group.

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Objectives: Ethanol is well-known to impair driving ability. The major aim of this study was to evaluate the number of drivers driving under the influence of ethanol in a population of randomly controlled drivers. Methods: 1016 drivers were randomly controlled at 27 different locations in Western Switzerland from October 2006 to April 2008. Drivers were controlled for alcohol consumption with a breathalyzer according to the Swiss Road traffic law. If the result was equal or higher than an equivalent of a blood alcohol concentration of 0.8 g/kg, a blood sample was taken; otherwise, a saliva sample was obtained. Blood and saliva were analysed for ethanol by Head-space gas chromatography coupled with a FID detector. Results: Among the controlled drivers, men (69%) predominated over female (31%). The mean age was 41 (range: 16 90). For 968 drivers (95.3%) ethanol was not detected in blood or saliva. These drivers were not under the influence of ethanol. Ethanol was detected in saliva or blood of 48 drivers (4.7%). Among these drivers, blood alcohol concentration (BAC) was above the legal limit of 0.8 g/kg (serious offence) in 14 cases (1.4% of the total population). BAC were in the range of 0.91 to 2.43 g/kg (mean: 1.32 g/kg, median: 1.11 g/kg). Among these 14 cases, men (13 cases, 93%) were over represented. No ethanol was found in the population of truck drivers (17 cases). 986 drivers were car drivers and 46 of them have drunk ethanol (5%). 13 bikers were controlled and 2 of them have drunk ethanol (15%). Conclusion: Driving under the influence of ethanol concerned about 5% of a population of randomly controlled drivers, and 1,4% of the drivers had a blood alcohol concentration higer than 0.8 g/kg (legale limit for a serious offence).

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A common way to model multiclass classification problems is by means of Error-Correcting Output Codes (ECOCs). Given a multiclass problem, the ECOC technique designs a code word for each class, where each position of the code identifies the membership of the class for a given binary problem. A classification decision is obtained by assigning the label of the class with the closest code. One of the main requirements of the ECOC design is that the base classifier is capable of splitting each subgroup of classes from each binary problem. However, we cannot guarantee that a linear classifier model convex regions. Furthermore, nonlinear classifiers also fail to manage some type of surfaces. In this paper, we present a novel strategy to model multiclass classification problems using subclass information in the ECOC framework. Complex problems are solved by splitting the original set of classes into subclasses and embedding the binary problems in a problem-dependent ECOC design. Experimental results show that the proposed splitting procedure yields a better performance when the class overlap or the distribution of the training objects conceal the decision boundaries for the base classifier. The results are even more significant when one has a sufficiently large training size.

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The pion spectrum for charged and neutral pions is investigated in pure neutron matter, by letting the pions interact with a neutron Fermi sea in a self-consistent scheme that renormalizes simultaneously the mesons, considered the source of the interaction, and the nucleons. The possibility of obtaining different kinds of pion condensates is investigated with the result that they cannot be reached even for values of the spin-spin correlation parameter, g', far below the range commonly accepted.

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We show that the dispersal routes reconstruction problem can be stated as an instance of a graph theoretical problem known as the minimum cost arborescence problem, for which there exist efficient algorithms. Furthermore, we derive some theoretical results, in a simplified setting, on the possible optimal values that can be obtained for this problem. With this, we place the dispersal routes reconstruction problem on solid theoretical grounds, establishing it as a tractable problem that also lends itself to formal mathematical and computational analysis. Finally, we present an insightful example of how this framework can be applied to real data. We propose that our computational method can be used to define the most parsimonious dispersal (or invasion) scenarios, which can then be tested using complementary methods such as genetic analysis.