Information integrity is a vital security property in a variety of applications. However, there is more than one facet to integrity: interpretations of integrity in different contexts include integrity via information flow, where the key is that trusted output is independent from untrusted input, and integrity via invariance, where the key is preservation of an invariant. Furthermore, integrity...

A closed-form multi-dimensional multi-invariance generalization of the ESPRIT algorithm is introduced to exploit the entire invariance structure underlying a (possibly) multiparametric data model, thereby greatly improving estimation performance. The multiple-invariance data structure that this proposed method can handle includes: (1) multiple occurrence of one size of invariance along one or m...

This study suggests two approaches to factorial invariance testing with multilevel data when the groups are at the within level: multilevel factor mixture model for known classes (ML FMM) and multilevel multiple indicators multiple causes model (ML MIMIC). The adequacy of the proposed approaches was investigated using Monte Carlo simulations. Additionally, the performance of different types of ...

The paper discusses the invariance view of reality: a view inspired by the relativity and quantum theory. It is an attempt to show that both versions of Structural Realism (epistemological and ontological) are already embedded in the invariance view but in each case the invariance view introduces important modifications. From the invariance view we naturally arrive at a consideration of symmetr...

A critical sub-process of category learning is detecting the invariance between categorical members. To examine brain activation associated with invariance detection at different steps of category learning, a stepwise category induction task was used in the present study. Within each trial, three stimuli were displayed sequentially, and participants were asked to learn the target category corre...