Search results for "S'"
showing 10 items of 706 documents
CCDC 644674: Experimental Crystal Structure Determination
2008
Related Article: M.L.Calatayud, I.Castro, M.Julve, J.Sletten|2008|J.Mol.Struct.|876|328|doi:10.1016/j.molstruc.2007.07.001
Algo más que el adiós al marxismo. El XXVIII Congreso del PSOE y el derecho de autodeterminación
2021
El XXVIII Congreso del Partido Socialista Obrero Español, celebrado en mayo de 1979, ha sido recordado por la célebre renuncia de Felipe González a la Secretaría General. El PSOE se había reafirmado como marxista y González acababa de perder el debate nominalista sobre la definición del partido. Aquel impacto emocional y mediático permitió ocultar tras los fuegos de artificio otros debates de mayor trascendencia práctica que también se dieron cita en aquel encuentro. Entre ellos, el que tenía que ver con su modelo de política autonómica. Desde 1979 estaba en juego cómo iba a construirse el Estado de las Autonomías, y el PSOE tenía la oportunidad de establecer en la resolución sobre autonomí…
A Space-Vector State Dynamic Model of the Synchronous Reluctance Motor Including Self and Cross-Saturation Effects and its Parameters Estimation
2018
This paper proposes a space-vector dynamic model of the Synchronous Reluctance Motor (SynRM) including both self-saturation and cross-saturation effects and selecting as state variables the stator currents. The proposed dynamic model is based on an original function between the stator flux and stator current components, and relies on 8 coefficients (fewer than other models in the scientific literature), presenting an interesting physical interpretation. Starting from this approach, both the static and dynamic inductances expressions of the model have been analytically developed, so that the reciprocity conditions for the cross saturation is satisfied. This paper presents also a technique fo…
Space-vector State Dynamic Model of the Synchronous Reluctance Motor Considering Self, Cross-Saturation and Iron Losses
2021
This paper proposes a space-vector dynamic model of the Synchronous Reluctance Motor (SynRM) including both self-saturation, cross-saturation effects, and iron losses expressed in state form, where the magnetizing current has been selected as a state variable. The proposed dynamic model is based on an original function between the stator flux and the magnetizing current components, improving a previously developed magnetic model. Additionally, the proposed model includes, besides the magnetic saturation, also iron losses. The proposed model requires 11 coefficients, among which 6 describe the self-saturation on both axes and 5 describe the cross-saturation. Starting from the definition of a…
An association model for bivariate data with application to the anlysis of university students' success.
2015
The academic success of students is a priority for all universities. We analyze the students' success at university by considering their performance in terms of both ‘qualitative performance’, measured by their mean grade, and ‘quantitative performance’, measured by university credits accumulated. These data come from an Italian University and concern a cohort of students enrolled at the Faculty of Economics. To jointly model both the marginal relationships and the association structure with covariates, we fit a bivariate ordered logistic model by penalized maximum likelihood estimation. The penalty term we use allows us to smooth the association structure and enlarge the range of possible …
A Bayesian Sequential Look at u-Control Charts
2005
We extend the usual implementation of u-control charts (uCCs) in two ways. First, we overcome the restrictive (and often inadequate) assumptions of the Poisson model; next, we eliminate the need for the questionable base period by using a sequential procedure. We use empirical Bayes(EB) and Bayes methods and compare them with the traditional frequentist implementation. EB methods are somewhat easy to implement, and they deal nicely with extra-Poisson variability (and, at the same time, informally check the adequacy of the Poisson assumption). However, they still need the base period. The sequential, full Bayes approach, on the other hand, also avoids this drawback of traditional u-charts. T…
Breaking the curse of dimensionality in quadratic discriminant analysis models with a novel variant of a Bayes classifier enhances automated taxa ide…
2013
Macroinvertebrate samples are commonly used in biomonitoring to study changes on aquatic ecosystems. Traditionally, specimens are identified manually to taxa by human experts being time-consuming and cost intensive. Using the image data of 35 taxa and 64 features, we propose a novel variant of the quadratic discriminant analysis for breaking the curse of dimensionality in quadratic discriminant analysis models. Our variant, called a random Bayes array (RBA), uses bagging and random feature selection similar to random forest. We explore several variations of RBA. We consider three classification (i.e taxa identification) decisions: majority vote, averaged posterior probabilities, and a novel…
Bayesian subset selection for additive and linear loss function
1979
Given k independent samples of common size n from k populations πj,…,πk with distribution the problem is to select a non-empty subset form {πj,…,πk}, which is associated with "good" (large) θ-values. We consider this problem from a Bayesian approach. By choosing additive and especially linear loss functions we try to fill a gap lying in between the results of Deely and Gupta (1968) and more recent papers due to Goel and Rubin (1977), Gupta and Hsu (1978) and other authors. It is shown that under acertain "normal model" Seal's procedure turns out to be Bayes w.r.t. an unrealistic loss function where as Gupta's maximunl means procedure turns out to be ( for large n) asymptotically Bayes w.r. …
Pathway analysis of high-throughput biological data within a Bayesian network framework
2011
Abstract Motivation: Most current approaches to high-throughput biological data (HTBD) analysis either perform individual gene/protein analysis or, gene/protein set enrichment analysis for a list of biologically relevant molecules. Bayesian Networks (BNs) capture linear and non-linear interactions, handle stochastic events accounting for noise, and focus on local interactions, which can be related to causal inference. Here, we describe for the first time an algorithm that models biological pathways as BNs and identifies pathways that best explain given HTBD by scoring fitness of each network. Results: Proposed method takes into account the connectivity and relatedness between nodes of the p…
Bayesian Markov switching models for the early detection of influenza epidemics
2008
The early detection of outbreaks of diseases is one of the most challenging objectives of epidemiological surveillance systems. In this paper, a Markov switching model is introduced to determine the epidemic and non-epidemic periods from influenza surveillance data: the process of differenced incidence rates is modelled either with a first-order autoregressive process or with a Gaussian white-noise process depending on whether the system is in an epidemic or in a non-epidemic phase. The transition between phases of the disease is modelled as a Markovian process. Bayesian inference is carried out on the former model to detect influenza epidemics at the very moment of their onset. Moreover, t…