CSL model checking of Deterministic and Stochastic Petri Nets

Deterministic and Stochastic Petri Nets (DSPNs) are a widely used high-level formalism for modeling discrete-event systems where events may occur either without consuming time, after a deterministic time, or after an exponentially distributed time. The underlying process dened by DSPNs, under certain restrictions, corresponds to a class of Markov Regenerative Stochastic Processes (MRGP). In this paper, we investigate the use of CSL (Continuous Stochastic Logic) to express probabilistic properties, such a time-bounded until and time-bounded next, at the DSPN level. The verication of such properties requires the solution of the steady-state and transient probabilities of the underlying MRGP. We also address a number of semantic issues regarding the application of CSL on MRGP and provide numerical model checking algorithms for this logic. A prototype model checker, based on SPNica, is also described

MathMC: A mathematica-based tool for CSL model checking of deterministic and stochastic Petri nets

Deterministic and Stochastic Petri Nets (DSPNs) are a widely used high-level formalism for modeling discreteevent systems where events may occur either without consuming time, after a deterministic time, or after an exponentially distributed time. CSL (Continuous Stochastic Logic) is a (branching) temporal logic developed to express probabilistic properties in continuous time Markov chains (CTMCs). In this paper we present a Mathematica-based tool that implements recent developments for model checking CSL style properties on DSPNs. Furthermore, as a consequence of the type of process underlying DSPNs (a superset of Markovian processes), we are also able to check CSL properties of Generalized Stochastic Petri Nets (GSPNs) and labeled CTMCs

Recurrent schizophrenia-like psychosis as first manifestation of epilepsy: a diagnostic challenge in neuropsychiatry

Abstract: Since the 1950s, several studies have been carried out to investigate the occurrence of schizophrenia-like psychoses in epilepsy. The psychopathological profile comprises symptoms from the affective, schizophrenic, and cognitive domains and the prevalence varies between 2% to 20%. Classification of such conditions is performed according to their temporal relationship with the seizure itself. Although it is well known that epilepsy may be associated with psychotic disorders, it is less widely recognized that relapsing psychotic phenomena may be the first and only symptom of epilepsy. In this research, two patients are described who were initially referred for recurrent episodes of bipolar affective disorder and schizophrenic psychosis, respectively. In both patients, a diagnosis of relapsing postictal psychotic states due to previously undiagnosed epilepsy was made and consequently, treatment with antiepileptics was started. During follow up over several months, they remained free of both epileptic and psychotic symptoms. Given the kaleidoscopic nature of the postictal psychosis and full recovery from this, such psychoses best meet the criteria for a cycloid psychosis. These observations illustrate diagnostic and therapeutic pitfalls due to the conceptual disintegration emerging from the inadequate separation between psychiatry and neurology. Therefore, the importance of a neuropsychiatric viewpoint should be promoted

Does gravity prefer the Poincare dodecahedral space?

The missing fluctuations problem in cosmic microwave background observations is naturally explained by well-proportioned small universe models. Among the well-proportioned models, the Poincare dodecahedral space is empirically favoured. Does gravity favour this space? The residual gravity effect is the residual acceleration induced by weak limit gravity from multiple topological images of a massive object on a nearby negligible mass test object. At the present epoch, the residual gravity effect is about a million times weaker in three of the well-proportioned spaces than in ill-proportioned spaces. However, in the Poincare space, the effect is 10,000 times weaker still, i.e. the Poincare space is about 10^{10} times "better balanced" than ill-proportioned spaces. Both observations and weak limit dynamics select the Poincare space to be special.Comment: 6 pages, Honorable Mention in 2009 Gravity Research Foundation essay competitio

Native Directly Follows Operator

Typical legacy information systems store data in relational databases. Process mining is a research discipline that analyzes this data to obtain insights into processes. Many different process mining techniques can be applied to data. In current techniques, an XES event log serves as a basis for analysis. However, because of the static characteristic of an XES event log, we need to create one XES file for each process mining question, which leads to overhead and inflexibility. As an alternative, people attempt to perform process mining directly on the data source using so-called intermediate structures. In previous work, we investigated methods to build intermediate structures on source data by executing a basic SQL query on the database. However, the nested form in the SQL query can cause performance issues on the database side. Therefore, in this paper, we propose a native SQL operator for direct process discovery on relational databases. We define a native operator for the simplest form of the intermediate structure, called the "directly follows relation". This approach has been evaluated with big event data and the experimental results show that it performs faster than the state-of-the-art of database approaches.Comment: 12 page

Guest editorial to the first international workshop on performability modelling of computer and communication systems

The papers in this issue of Performance Evaluation all deal with performability modelling of computer and communication systems. This was the topic of the First International Workshop on Performability Modelling of Computer and Communication Systems (PMCCS-1), held 7-8 February 1991, at the University of Twente, Enschede, the Netherlands