OBJECTIVES To derive a prediction rule using data available in the emergency department (ED) to identify a group of patients hospitalized for the treatment of heart failure who are at low risk of death and serious complications. METHODS The authors analyzed data for all 33,533 patients with a primary hospital discharge diagnosis of heart failure in 1999 who were admitted from EDs in Pennsylva...

Predicting failures at runtime is one of the most promising techniques to increase the availability of computer systems. However, failure prediction algorithms are still far from providing satisfactory results. In particular, the identification of the variables that show symptoms of incoming failures is a difficult problem. In this paper we propose an approach for identifying the most adequate ...

 In this paper, a new Dynamic Geometric Genetic Programming (DGGP) technique is applied to empirical analysis of financial ratios and bankruptcy prediction. Financial ratios are indeed desirable for prediction of corporate bankruptcy and identification of firms’ impending failure for investors, creditors, borrowing firms, and governments. By the time, several methods have been attempted in...

Protein domain prediction is important for protein structure prediction, structure determination, function annotation, mutagenesis analysis and protein engineering. Here we describe an accurate protein domain prediction server (DOMAC) combining both template-based and ab initio methods. The preliminary version of the server was ranked among the top domain prediction servers in the seventh editi...

Performance analysis and formal correctness veri-cation of computer communication protocols and distributed systems have traditionally been considered as two separate elds. However, their integration can be achieved by using formal description techniques as paradigms for performance modeling. This paper investigates the possibility of using LOTOS, one of the two formal speciication languages th...

Conditional Random Fields (CRFs) are a popular formalism for structured prediction in NLP. It is well known how to train CRFs with certain topologies that admit exact inference, such as linear-chain CRFs. Some NLP phenomena, however, suggest CRFs with more complex topologies. Should such models be used, considering that they make exact inference intractable? Stoyanov et al. (2011) recently argu...

In our mission to advance innovation by industrial adoption of academic results, we perform many projects with high-tech industries. Favoring formal methods, we observe a gap between industrial needs in performance modeling and the analysis capabilities of formal methods for this goal. After clarifying this gap, we highlight some relevant deficiencies for state-of-the-art quantitative analysis ...

At the heart of numerical weather prediction algorithms lie a Laplace and positive definite Helmholtz problems on the sphere [12]. Recently, there has been interest in using finite elements [2] and domain decomposition methods [1, 10]. The Schwarz iteration [7, 8, 9] and its variants [9, 4, 5, 6, 3, 11] are popular domain decomposition methods. In this paper, we introduce improved transmission ...

The primary interest of the paper is to apply a two-time-level split explicit time scheme developed by one of the authors to the Lokal-Modell (LM) of the German Weather Service (DWD). This model belongs to the operational NWP system at DWD, which makes it particularly interesting for this study. To better understand the implementation of this time scheme in a compressible nonhydrostatic model t...

The Protein Structure Prediction (PSP) problem is concerned about the prediction of the native tertiary structure of a protein in respect to its amino acids sequence. PSP is a challenging and computationally open problem. Therefore, several researches and methodologies have been developed for it. In this way, developers are working to integrate frameworks in order to improve their capabilities ...