Estudi de xarxes WPAN 802.15.4

Aquest projecte proposa l'estudi en profunditat de les característiques de les xarxes WPAN 802.15.4 i de les xarxes ZigBee.

Vers un nou model psicopedagògic d'intervenció educativa

L'objectiu d'aquest article és el plantejament d'un Model d'intewenció Psicopedagògica en el Procés Educatiu que doni resposta a les necessitats educatives, en els cicles d'Educació Infantil i Primària, i amb capacitat d'adaptació als canvis, ara que la nova reforma del sistema educatiu comença a emmarcar la realitat educativa.La seva implantació és en realitat un fet palpable: durant el curs 92/93 s'inicia la sevaaplicació als alumnes del 2n Cicle de l'Ensenyament Infantil i als del lr de l'Ensenyament Primari

A unified approach for representing rows and columns in contingency tables

By using suitable parameters, we present a uni¯ed aproach for describing four methods for representing categorical data in a contingency table. These methods include:correspondence analysis (CA), the alternative approach using Hellinger distance (HD),the log-ratio (LR) alternative, which is appropriate for compositional data, and theso-called non-symmetrical correspondence analysis (NSCA). We then make an appropriate comparison among these four methods and some illustrative examples are given.Some approaches based on cumulative frequencies are also linked and studied usingmatrices.Key words: Correspondence analysis, Hellinger distance, Non-symmetrical correspondence analysis, log-ratio analysis, Taguchi inertia

On bounds for network revenue management

The Network Revenue Management problem can be formulated as a stochastic dynamic programming problem (DP or the\optimal" solution V *) whose exact solution is computationally intractable. Consequently, a number of heuristics have been proposed in the literature, the most popular of which are the deterministic linear programming (DLP) model, and a simulation based method, the randomized linear programming (RLP) model. Both methods give upper bounds on the optimal solution value (DLP and PHLP respectively). These bounds are used to provide control values that can be used in practice to make accept/deny decisions for booking requests. Recently Adelman [1] and Topaloglu [18] have proposed alternate upper bounds, the affine relaxation (AR) bound and the Lagrangian relaxation (LR) bound respectively, and showed that their bounds are tighter than the DLP bound. Tight bounds are of great interest as it appears from empirical studies and practical experience that models that give tighter bounds also lead to better controls (better in the sense that they lead to more revenue). In this paper we give tightened versions of three bounds, calling themsAR (strong Affine Relaxation), sLR (strong Lagrangian Relaxation) and sPHLP (strong Perfect Hindsight LP), and show relations between them. Speciffically, we show that the sPHLP bound is tighter than sLR bound and sAR bound is tighter than the LR bound. The techniques for deriving the sLR and sPHLP bounds can potentially be applied to other instances of weakly-coupled dynamic programming.

Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.

Catàleg de plantes vasculars endèmiques, rares o amenaçades de Catalunya. I. Tàxons endèmics

Catalogue of endemic, rare or threatened vascular plants in Catalonia. I. Endemic taxa. This is the first of a set of papers devoted to rare or threatened plants in Catalonia. We list 279 specific or subspecific taxa which are in a broad sense endemic to the northeastern part of the Iberian Peninsula. We assess them with regard to their conservation status according to IUCN criteria. Assignment of these taxa to established categories has led to the following results: 6 taxa critically endangered (CR), 5 endangered (EN), 32 vulnerable (VU), 5 near threatened (LR nt). 84 least concern (LR lc), 116 not threatened (NT) and 31 data deficient (DD). The small number of taxa that enjoy legal protection in comparison with the number of threatened plants is emphasized. Key words: Endemic plants, Catalonia, Plant conservation, UICN categories.

Stratification of the severity of critically ill patients with classification trees

Background: Development of three classification trees (CT) based on the CART (Classification and Regression Trees), CHAID (Chi-Square Automatic Interaction Detection) and C4.5 methodologies for the calculation of probability of hospital mortality; the comparison of the results with the APACHE II, SAPS II and MPM II-24 scores, and with a model based on multiple logistic regression (LR). Methods: Retrospective study of 2864 patients. Random partition (70:30) into a Development Set (DS) n = 1808 and Validation Set (VS) n = 808. Their properties of discrimination are compared with the ROC curve (AUC CI 95%), Percent of correct classification (PCC CI 95%); and the calibration with the Calibration Curve and the Standardized Mortality Ratio (SMR CI 95%). Results: CTs are produced with a different selection of variables and decision rules: CART (5 variables and 8 decision rules), CHAID (7 variables and 15 rules) and C4.5 (6 variables and 10 rules). The common variables were: inotropic therapy, Glasgow, age, (A-a)O2 gradient and antecedent of chronic illness. In VS: all the models achieved acceptable discrimination with AUC above 0.7. CT: CART (0.75(0.71-0.81)), CHAID (0.76(0.72-0.79)) and C4.5 (0.76(0.73-0.80)). PCC: CART (72(69- 75)), CHAID (72(69-75)) and C4.5 (76(73-79)). Calibration (SMR) better in the CT: CART (1.04(0.95-1.31)), CHAID (1.06(0.97-1.15) and C4.5 (1.08(0.98-1.16)). Conclusion: With different methodologies of CTs, trees are generated with different selection of variables and decision rules. The CTs are easy to interpret, and they stratify the risk of hospital mortality. The CTs should be taken into account for the classification of the prognosis of critically ill patients.

Short communication. Potential to mitigate anthropogenic CO2 emissions by tillage reduction in dryland soils of Spain

Spain is one of the countries with the highest greenhouse gas (GHG) emissions within the EU-27. Consequently, mitigation strategies need to be reported and quantified to accomplish the goals and requirements of the Kyoto Protocol. In this study, a first estimation of the carbon (C) mitigation potential of tillage reduction in Mediterranean rainfed Spain is presented. Results from eight studies carried out in Spain under rainfed agriculture to investigate the effects of no-tillage (NT) and reduced tillage (RT) compared with conventional tillage (CT) on soil organic carbon (SOC) were used. For current land surface under conservation tillage, NT and RT are sequestering 0.14 and 0.08 Tg C yr-1, respectively. Those rates represent 1.1% and 0.6% of the total CO2 emissions generated from agricultural activities in Spain during 2006. Alternatively, in a hypothetical scenario where all the arable dryland was under either NT or RT management, SOC sequestration would be 2.18 and 0.72 Tg C yr-1 representing 17.4% and 5.8% of the total 2006 CO2 equivalent emissions generated from the agricultural sector in Spain. This is a significant estimate that would help to achieve GHG emissions targets for the current commitment period of the Kyoto Protocol.