Over-approximating the set of all reachable states of a given system is an important task for the verification of safety properties. Such an unbounded time verification is in particular challenging for hybrid systems. We recently developed an algorithm that over-approximates the set of all reachable states of a given affine hybrid automata by performing linear template-based abstract interpreta...

Hybrid systems are dynamical systems with the ability to describe mixed discretecontinuous evolution of a wide range of systems. Consequently, at first glance, hybrid systems appear powerful but recalcitrant, neither yielding to analysis and reasoning through a purely continuous-time modeling as with systems of differential equations, nor open to inferential processes commonly used for discrete...

We show how some graph theoretical arguments may be used to reduce the complexity of the computation of the steady-state distribution of Markov chain. We consider the directed graph associated to a Markov chain derived from a Stochastic Automata Network (SAN). The structural properties of the automata are used to establish new various results. First, we establish the complexity of the resolutio...

In this paper we extend the predicate logic introduced in [BRS02] in order to deal with Semi-Markov Processes. We prove that with respect to qualitative probabilistic properties, model checking is decidable for this logic applied to Semi-Markov Processes. Furthermore we apply our logic to Probabilistic Timed Automata considering classical and urgent semantics, and considering also predicates on...

Hybrid automata are the prevailing formalisms to reason about systems that consist of discrete and continuous functions. Several specializations like o-minimal hybrid automata have been considered that should (1) retain as much expressibility as possible, and (2) lead to decidable (reachability) problems. However, the discrete transitions of o-minimal automata require constant resets of the con...

Image segmentation is an important task in image processing and computer vision which attract many researchers attention. There are a couple of information sets pixels in an image: statistical and structural information which refer to the feature value of pixel data and local correlation of pixel data, respectively. Markov random field (MRF) is a tool for modeling statistical and structural inf...

Planning in hybrid domains is an important and challenging task, and various planning algorithms have been proposed in the last years. From an abstract point of view, hybrid planning domains are based on hybrid automata, which have been studied intensively in the model checking community. In particular, powerful model checking algorithms and tools have emerged for this formalism. However, despi...

Biological systems can possess multiple operational modes with specific nonlinear dynamics in each mode. Hybrid automata and its variants are often used to model and analyze the dynamics of such systems. Highly nonlinear hybrid automata are difficult to analysis and usually have many parameters. An important problem is to identify parameter values using which the system can reach certain states...

In this paper we develop data mining techniques to predict 3D contact potentials among protein residues (or amino acids) based on the hierarchical nucleation-propagation model of protein folding. We apply a hybrid approach, using a hidden Markov model to extract folding initiation sites, and then apply association mining to discover contact potentials. The new hybrid approach achieves accuracy ...

This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-economic variables dealing with urban sprawl were operationalised to create a probability surface of...