The context-tree weighting method (Willems, Shtarkov, and Tjalkens [1995]) is a sequential universal source coding method that achieves the Rissanen lower bound [1984] for tree sources. The same authors also proposed context-tree maximizing, a two-pass version of the context-tree weighting method [1993]. Later Willems and Tjalkens [1998] described a method based on ratios (betas) of sequence pr...

Abstract This paper proposes a multi-criteria decision-making method for new energy power station site selection based on fuzzy comprehensive analysis method. It is applied to make decisions the target location when selecting address building station, ensure reasonableness of corresponding weights each index, and give reasonable scientific suggestions decision-makers obtain expected results. We...

Performance evaluation of various organizations especially educational institutions is a very important area of research and needs to be cultivated more. In this paper, we propose a performance evaluation for educational institutions using rough set on fuzzy approximation spaces with ordering rules and information entropy. In order to measure the performance of educational institutions, we cons...

16 This paper describes the results of research designed to explore reporting of three indices 17 (Corruption Perception Index, CPI, Human Development Index, HDI and the Ecological 18 Footprint, EF) in the UK national press between January 1990 and December 2009. 19 Reporting of the indices was assessed by: 20 (a) the number of articles published each year mentioning the index at least once 21 ...

Social Deprivation and Exclusion of Immigrants in Germany This paper aims at providing empirical evidence on social exclusion of immigrants in Germany. We demonstrate that when using a conventional definition of the social inclusion index typically applied in the literature, immigrants appear to experience a significant degree of social deprivation and exclusion, confirming much of the economic...

The integrated biological data is expected to obtain a higher exactness, better performance and greater robustness compared to single dataset. In this work, we present data integration using kernel-based approach to identify protein class in yeast, ribosomal proteins and membrane proteins. By using intermediate stage of integration, we change the single data source into kernel matrix format. Ke...

This paper looks at unobserved components models and examines the implied weighting patterns for signal extraction. There are three main themes. The rst is the implications of correlated disturbances driving the components, especially those cases in which the correlation is perfect. The second is how setting up models with t distributed disturbances leads to weighting patterns which are robust ...