Knowledge based systems need to deal with aggregation and fusion of data with uncertainty. To use many sources of information in numerical forms for the purpose of decision or conclusion, systems suppose to have tools able to represent the knowledge in a mathematical form. One of the solutions is to use fuzzy logic operators. We present in this article an improvement of the triple Π operator in...

This article discusses the meta-analysis of raw mean differences. It presents a rationale for cumulating psychological effects in a raw metric and compares raw mean differences to standardized mean differences. Some limitations of standardization are noted, and statistical techniques for raw meta-analysis are described. These include a graphical device for decomposing effect sizes. Several illu...

We study a Mean-Risk model derived from a behavioral theory of Disappointment with multiple reference points. One distinguishing feature of the risk measure is that it is based on mutual deviations of outcomes, not deviations from a specific target. We prove necessary and sufficient conditions for strict first and second order stochastic dominance, and show that the model is, in addition, a Con...

Principal Component Analysis (PCA) is the most widely used unsupervised dimensionality reduction approach. In recent research, several robust PCA algorithms were presented to enhance the robustness of PCA model. However, the existing robust PCA methods incorrectly center the data using the `2-norm distance to calculate the mean, which actually is not the optimal mean due to the `1-norm used in ...

For low dimensional systems, (i.e. 2D and, to a certain extent, 1D) it is proved that mean–field theory can provide an asymptotic guideline to the phase structure of actual systems. In particular, for attractive pair interactions that are sufficiently “spead out” according to an exponential (Yukawa) potential it is shown that the energy, free energy and, in particular, the block magnetization (...