From capital surges to drought: seeking stability for emerging economies

Includes bibliography

Risk prediction for weed infestation using classification rules

This paper proposes a fuzzy classification system for the risk of infestation by weeds in agricultural zones considering the variability of weeds. The inputs of the system are features of the infestation extracted from estimated maps by kriging for the weed seed production and weed coverage, and from the competitiveness, inferred from narrow and broad-leaved weeds. Furthermore, a Bayesian network classifier is used to extract rules from data which are compared to the fuzzy rule set obtained on the base of specialist knowledge. Results for the risk inference in a maize crop field are presented and evaluated by the estimated yield loss. © 2009 IEEE.

Optimal clone identifier based on dynamic rules and process algebra

The rule creation to clone selection in different projects is a hard task to perform by using traditional implementations to control all the processes of the system. The use of an algebraic language is an alternative approach to manage all of system flow in a flexible way. In order to increase the power of versatility and consistency in defining the rules for optimal clone selection, this paper presents the software OCI 2 in which uses process algebra in the flow behavior of the system. OCI 2, controlled by an algebraic approach was applied in the rules elaboration for clone selection containing unique genes in the partial genome of the bacterium Bradyrhizobium elkanii Semia 587 and in the whole genome of the bacterium Xanthomonas axonopodis pv. citri. Copyright© (2009) by the International Society for Research in Science and Technology.

Selección de documentos y publicaciones de la División de Desarrollo Social de la CEPAL = Selection of documents and publications of ECLAC's Social Development Division

Publicación bilingüe

Selección de documentos y publicaciones de la División de Desarrollo Social de la CEPAL: octubre-diciembre 1995 = Selection of documents and publications of ECLAC's Social Development Division: October-December 1995

Publicación bilingüe

Catálogo de publicaciones, 1988-1998 de la Dirección de Proyectos y Programación de Inversiones del ILPES = Publications catalogue, 1988-1998 of Projects and Investments Programming Division

Títulos de documentos en español y/o inglés

Catálogo de publicaciones, 1988-1999, de la Dirección de Proyectos y Programación de Inversiones del ILPES = Publications catalogue, 1988-1999, of Projects and Investments Programming Division

Títulos de documentos en español y/o inglés

Multilateral rules on competition policy: an overview of the debate

Includes bibliography

Rules of origin and trade facilitation in preferential trade agreements in Latin America

Includes bibliography

Trade and investment rules: Latin American perspectives

Includes bibliography

Selecting candidate labels for hierarchical document clusters using association rules

One way to organize knowledge and make its search and retrieval easier is to create a structural representation divided by hierarchically related topics. Once this structure is built, it is necessary to find labels for each of the obtained clusters. In many cases the labels have to be built using only the terms in the documents of the collection. This paper presents the SeCLAR (Selecting Candidate Labels using Association Rules) method, which explores the use of association rules for the selection of good candidates for labels of hierarchical document clusters. The candidates are processed by a classical method to generate the labels. The idea of the proposed method is to process each parent-child relationship of the nodes as an antecedent-consequent relationship of association rules. The experimental results show that the proposed method can improve the precision and recall of labels obtained by classical methods. © 2010 Springer-Verlag.

Democratic governance and gender: possible linkages

Includes bibliography

Fiscal rules and countercyclical policy: Frank Ramsey meets Gramm-Rudman-Hollings

Incluye Bibliografía

Fiscal rules for subnational governments in the EMU context

Includes bibliography

Comparative study of algorithms for mining association rules: Traditional approach versus multi-relational approach

The multi-relational Data Mining approach has emerged as alternative to the analysis of structured data, such as relational databases. Unlike traditional algorithms, the multi-relational proposals allow mining directly multiple tables, avoiding the costly join operations. In this paper, is presented a comparative study involving the traditional Patricia Mine algorithm and its corresponding multi-relational proposed, MR-Radix in order to evaluate the performance of two approaches for mining association rules are used for relational databases. This study presents two original contributions: the proposition of an algorithm multi-relational MR-Radix, which is efficient for use in relational databases, both in terms of execution time and in relation to memory usage and the presentation of the empirical approach multirelational advantage in performance over several tables, which avoids the costly join operations from multiple tables. © 2011 IEEE.