943 resultados para statistical softwares


Relevância:

20.00% 20.00%

Publicador:

Resumo:

Statistical Report On FIP Applications And Cases Discontinued

Relevância:

20.00% 20.00%

Publicador:

Resumo:

A-1 Monthly Public Assistance Statistical Report Family Investment Program

Relevância:

20.00% 20.00%

Publicador:

Resumo:

A-7 Statistical Report On FIP Applications And Cases Discontinued

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Monthly Public Assistance Statistical Report Family Investment Program

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Monthly Public Assistance Statistical Report Family Investment Program

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Statistical Report On FIP Applications And Cases Discontinued

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Statistical Report On FIP Applications And Cases Discontinued

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Background: Recent advances on high-throughput technologies have produced a vast amount of protein sequences, while the number of high-resolution structures has seen a limited increase. This has impelled the production of many strategies to built protein structures from its sequence, generating a considerable amount of alternative models. The selection of the closest model to the native conformation has thus become crucial for structure prediction. Several methods have been developed to score protein models by energies, knowledge-based potentials and combination of both.Results: Here, we present and demonstrate a theory to split the knowledge-based potentials in scoring terms biologically meaningful and to combine them in new scores to predict near-native structures. Our strategy allows circumventing the problem of defining the reference state. In this approach we give the proof for a simple and linear application that can be further improved by optimizing the combination of Zscores. Using the simplest composite score () we obtained predictions similar to state-of-the-art methods. Besides, our approach has the advantage of identifying the most relevant terms involved in the stability of the protein structure. Finally, we also use the composite Zscores to assess the conformation of models and to detect local errors.Conclusion: We have introduced a method to split knowledge-based potentials and to solve the problem of defining a reference state. The new scores have detected near-native structures as accurately as state-of-art methods and have been successful to identify wrongly modeled regions of many near-native conformations.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

A-1 Monthly Public Assistance Statistical Report Family Investment Program, June 2005

Relevância:

20.00% 20.00%

Publicador:

Resumo:

A-7 Statistical Report On FIP Applications And Cases Discontinued, June 2005

Relevância:

20.00% 20.00%

Publicador:

Resumo:

A-1 Monthly Public Assistance Statistical Report Family Investment Program, July 2005

Relevância:

20.00% 20.00%

Publicador:

Resumo:

A-7 Statistical Report On FIP Applications And Cases Discontinued, July 2005

Relevância:

20.00% 20.00%

Publicador:

Resumo:

A-1 Monthly Public Assistance Statistical Report Family Investment Program, August 2005

Relevância:

20.00% 20.00%

Publicador:

Resumo:

For single-user MIMO communication with uncoded and coded QAM signals, we propose bit and power loading schemes that rely only on channel distribution information at the transmitter. To that end, we develop the relationship between the average bit error probability at the output of a ZF linear receiver and the bit rates and powers allocated at the transmitter. This relationship, and the fact that a ZF receiver decouples the MIMO parallel channels, allow leveraging bit loading algorithms already existing in the literature. We solve dual bit rate maximization and power minimization problems and present performance resultsthat illustrate the gains of the proposed scheme with respect toa non-optimized transmission.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

In this article we present a hybrid approach for automatic summarization of Spanish medical texts. There are a lot of systems for automatic summarization using statistics or linguistics, but only a few of them combining both techniques. Our idea is that to reach a good summary we need to use linguistic aspects of texts, but as well we should benefit of the advantages of statistical techniques. We have integrated the Cortex (Vector Space Model) and Enertex (statistical physics) systems coupled with the Yate term extractor, and the Disicosum system (linguistics). We have compared these systems and afterwards we have integrated them in a hybrid approach. Finally, we have applied this hybrid system over a corpora of medical articles and we have evaluated their performances obtaining good results.