Classification of Incomplete Data Using the Fuzzy ARTMAP Neural Network

The fuzzy ARTMAP neural network is used to classify data that is incomplete in one or more ways. These include a limited number of training cases, missing components, missing class labels, and missing classes. Modifications for dealing with such incomplete data are introduced, and performance is assessed on an emitter identification task using a data base of radar pulsesDefense Advanced Research Projects Agency and the Office of Naval Research (N00014-95-1-0409) (S.G. and M.A.R); National Science Foundation (IRI-97-20333) (S.G.); Natural Sciences and Engineerging Research Council of Canada (E.G.); Office of Naval Research (N00014-95-1-0657

Comparison of Classifiers for Radar Emitter Type Identification

ARTMAP neural network classifiers are considered for the identification of radar emitter types from their waveform parameters. These classifiers can represent radar emitter type classes with one or more prototypes, perform on-line incremental learning to account for novelty encountered in the field, and process radar pulse streams at high speed, making them attractive for real-time applications such as electronic support measures (ESM). The performance of four ARTMAP variants- ARTMAP (Stage 1), ARTMAP-IC, fuzzy ARTMAP and Gaussian ARTMAP - is assessed with radar data gathered in the field. The k nearest neighbor (kNN) and radial basis function (RDF) classifiers are used for reference. Simulation results indicate that fuzzy ARTMAP and Gaussian ARTMAP achieve an average classification rate consistently higher than that of the other ARTMAP classifers and comparable to that of kNN and RBF. ART-EMAP, ARTMAP-IC and fuzzy ARTMAP require fewer training epochs than Gaussian ARTMAP and RBF, and substantially fewer prototype vectors (thus, smaller physical memory requirements and faster fielded performance) than Gaussian ARTMAP, RBF and kNN. Overall, fuzzy ART MAP performs at least as well as the other classifiers in both accuracy and computational complexity, and better than each of them in at least one of these aspects of performance. Incorporation into fuzzy ARTMAP of the MT- feature of ARTMAP-IC is found to be essential for convergence during on-line training with this data set.Defense Advanced Research Projects Agency and the Office of Naval Research (N000I4-95-1-409 (S.G. and M.A.R.); National Science Foundation (IRI-97-20333) (S.G.); Natural Science and Engineering Research Council of Canada (E.G.); Office of Naval Research (N00014-95-1-0657

Is Seasonal Adjustment a Linear or Nonlinear Data Filtering Process?

In this paper, we investigate whether seasonal adjustment procedures are, at least approximately, linear data transformations. This question is important with respect to many issues including estimation of regression models with seasonally adjusted data. We focus on the X-11 program and first review the features of the program that might be potential sources of nonlinearity. We rely on simulation evidence, involving linear unobserved component ARIMA models, to assess the adequacy of the linear approximation. We define a set of properties for the adequacy of a linear approximation to a seasonal adjustment filter. These properties are examined through statistical tests. Next, we study the effect of X-11 seasonal adjustment on regression statistics assessing the statistical significance of the relationship between economic variables in the same spirit as Sims (1974) and Wallis (1974). These findings are complemented with several empirical examples involving economic data. Nous examinons si la procédure d'ajustement X-11 est approximativement linéaire. Il y a potentiellement plusieurs sources de non-linéarité dans cette procédure. Le but de l'étude est de savoir si ces sources sont effectivement assez importantes pour affecter, par exemple, des résultats d'estimation dans des modèles de régression linéaire. La seule façon de répondre à cette question est par estimation. Nous proposons plusieurs critères qu'on peut utiliser pour juger si une procédure d'ajustement est approximativement linéaire. Nous examinons également par simulation des propriétés de tests dans le modèle de régression dans le même esprit que Sims (1974) et Wallis (1974).X-11 program; Nonlinearity, X-11 program ; Nonlinearity

The Political Dynamics of EU Human Rights Law: Scratching Beneath the Surface

https://www.e-elgar.com/shop/gbp/research-handbook-on-the-politics-of-eu-law-9781788971270.htm

Federalization through rights in the EU: A legal opportunities approach

https://www.elevenjournals.com/tijdschrift/ejlr/2018/2-3/EJLR_1387-2370_2018_020_002_00

The protection of civil rights and liberties and the transformation of Union citizenship

https://www.elgaronline.com/view/edcoll/9781788113632/9781788113632.00018.xm

Seasonal Adjustment and Volatility Dynamics

In this paper we try to enhance our understanding of the effect of filtering, particularly seasonal adjustment filtering, on the estimation of volatility models. We focus exclusively on ARCH models as a specific class of models and examine the effect of both linear and nonlinear filters on (seasonal) volatility dynamics. The case of linear filters is treated in a general abstract setting applicable to seasonal adjustment as well as various other linear filters often applied to transform raw data. Next we focus on specific cases like the first and seasonal differencing filters as well as the X-11 filter, both its linear representation and the (nonlinear) procedure implemented in practice. We uncover surprising features regarding the linear X-11 filter, e.g. it introduces a small seasonal pattern in volatility. More interestingly, we show that the linear X-11 and the actual procedure produce serious downward biases in ARCH effects and their persistence. Finally, we uncover important differences between the linear version of X-11 and the actual procedure. Nous étudions l'effet de filtre sur l'estimation de processus de type GARCH. Le cas du filtre linéaire est analysé dans un contexte général pour des processus GARCH faibles. Plusieurs cas spéciaux sont discutés, notamment ce-lui du filtre d'ajustement X-11 pour les effets saisonniers. Nous trouvons que ce filtre produit un effet de persistance saisonnière au niveau de la volatilité. Nous abordons ensuite le filtrage non linéaire dans le cas du filtre X-11. Une étude de Monte Carlo démontre qu'il y a des différences très importantes entre la représentation linéaire du filtre et le programme non linéaire appliqué aux données réelles.GARCH processes, seasonality, X-11, Processus GARCH, Saisonnalité, X-11

Influence of functional deficiency of complement mannose-binding lectin on outcome of patients with acute ST-elevation myocardial infarction undergoing primary percutaneous coronary intervention

Aims Experimental data point towards a favourable effect of low serum concentrations of complement mannose-binding lectin (MBL) on myocardial ischaemia/reperfusion (I/R) injury. As comparable data on the role of MBL in human I/R injury is lacking, we investigated the influence of low serum MBL concentrations on mortality of patients with acute ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI). Methods and results Mannose-binding lectin was determined in 890 acute STEMI patients that were prospectively recruited in the APEX-AMI trial. This trial had a primary endpoint of death through Day 30 and secondary endpoints of death through Day 90 and the composite of death, cardiogenic shock, or congestive heart failure (CHF) through Days 30 and 90. Samples were taken immediately before PCI and the analysis of MBL limited to patients having received placebo. Patients with serum MBL levels of or below 100 ng/mL were considered to be functionally deficient. Of the 890 patients, 127 had functional MBL deficiency (14.3%). Characteristics of patients with MBL deficiency and those with MBL levels >100 ng/mL did not differ. In patients with MBL deficiency, there was 1 death (0.79%) compared with 42 deaths (5.51%) in patients with MBL levels >100 ng/mL (P = 0.0233) representing an absolute and relative lower mortality in MBL deficient patients of 4.7 and 85%, respectively. Functional MBL deficiency, however, was not associated with decreased risk of the combined endpoints of death and shock or death, shock, and CHF, respectively. Conclusion Functional deficiency of complement MBL is associated with reduced mortality in patients with STEMI undergoing PCI. This unique finding suggests that a component of the innate immune system affects mortality in STEMI patients undergoing primary PCI. Trial Registration: clinicaltrials.gov, Identifier: NCT0009163

Report on mechanisms transposing and enforcing civil rights aiming at identifying barriers that EU citizens and third-country nationals face in gaining (cross-border) access to justice in selected EU Member States

http://beucitizen.eu/wp-content/uploads/D7.2_Report_final.pd