7 resultados para Classical particle

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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IARD 8th Biennial Conference on Classical and Quantum Relativistic Dynamics of Particles and Fields - Galileo Galilei Inst Theoret Phys (GGI), Florence, ITALY - MAY 29-JUN 01, 2012. Edited by:Horowitz, LP

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In this paper we introduce a new axiom, denoted claims separability, that is satisfied by several classical division rules defined for claims problems. We characterize axiomatically the entire family of division rules that satisfy this new axiom. In addition, employing claims separability, we characterize the minimal overlap rule, given by O'Neill (1982), Piniles rule and the rules in the TAL-family, introduced by Moreno-Ternero and Villar (2006), which includes the uniform gains rule, the uniform losses rule and the Talmud rule.

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Spanish Relativity Meeting (ERE 2014) Valencia, SPAIN, SEP 01-05, 2014

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Este trabajo ha sido realizado en el marco del PI UPV 106.130-HA092/99.

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In multisource industrial scenarios (MSIS) coexist NOAA generating activities with other productive sources of airborne particles, such as parallel processes of manufacturing or electrical and diesel machinery. A distinctive characteristic of MSIS is the spatially complex distribution of aerosol sources, as well as their potential differences in dynamics, due to the feasibility of multi-task configuration at a given time. Thus, the background signal is expected to challenge the aerosol analyzers at a probably wide range of concentrations and size distributions, depending of the multisource configuration at a given time. Monitoring and prediction by using statistical analysis of time series captured by on-line particle analyzers in industrial scenarios, have been proven to be feasible in predicting PNC evolution provided a given quality of net signals (difference between signal at source and background). However the analysis and modelling of non-consistent time series, influenced by low levels of SNR (Signal-Noise Ratio) could build a misleading basis for decision making. In this context, this work explores the use of stochastic models based on ARIMA methodology to monitor and predict exposure values (PNC). The study was carried out in a MSIS where an case study focused on the manufacture of perforated tablets of nano-TiO2 by cold pressing was performed

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9th Biennial Conference on Classical and Quantum Relativistic Dynamics of Particles and Fields (IARD)