spatial-temporal modeling of air pollutants, ground-level ozone concentrations in particular, has attracted recent attention because by using spatial-temporal modeling, can analyze, interpolate or predict ozone levels at any location. in this paper we consider daily averages of troposphere ozone over tehran city. for eliminating the trend of data, a dynamic linear model is used, then some featu...

We investigate the formal relationship between separability of processes and the types of non-interference properties they enjoy. Though intuitively appealing, separability – the ability to define a process as a parallel composition of disjoint components – alone cannot adequately prove the absence of information flow. We present a number of laws for the composition of secure systems, and an ex...

A state amalgamation of a directed graph is a node contraction which is only permitted under certain configurations of incident edges. In symbolic dynamics, state amalgamation and its inverse operation, state splitting, play a fundamental role in the the theory of subshifts of finite type (SFT): any conjugacy between SFTs, given as vertex shifts, can be expressed as a sequence of symbol splitti...

In remote sensing, the number of training samples is often limited. For hyperspectral data, it becomes more difficult to obtain accurate estimates of class statistics because of the small ratio of the training sample size to dimensionality. Generally speaking, classification performance depends on four factors: class separability, the training sample size, dimensionality, and classifier type (o...

In this paper we argue for a Separability Hypothesis as a working hypothesis for AI. There is no a priori equivalence of the terms “mind” and “cognition.” Phenomenologically, a mental state has a cognitive content as well as subjectivity and emotions. The Separability Hypothesis asserts that an architecture for intelligence is a homomorphism of the architecture for mind. None of the technical p...