Alternating-Time Temporal Logic (ATL) is a branching-time temporal logic that naturally describes computations of opensystems. An open system interacts with its environment and its behavior depends on the state of the system as well as the behavior of the environment. ATL model-checking is a well-established technique for verifying that a formal model representing such a system satisfies a given property. In this paper we describe a new interactive model checker environment based on algebraic approach. Our tool is implemented in clientserver paradigm. The client part allows an interactive construction of ATL models represented by concurrent game structures as directed multi-graphs. The server part embeds an ATL model checking algorithm implemented using ANTLR and Relational Algebra expressions translated into SQL queries. The server side of our tool was published as a Web service exposing its functionality to various clients through standard XML interfaces.

No abstract

The mentality of electricity consumers is one of the most important entities that must be addressed when dealing with issues in the operation of power systems. Consumers are used to being completely passive, but recently these things have changed as significant progress of Information and Communication Technologies (ICT) and Internet of Things (IoT) has gained momentum. In this paper, we propose a statistical measurement model using a covariance structure, specifically a first-order confirmatory factor analysis (CFA) using SAS CALIS procedure to identify the factors that could contribute to the change of attitude within energy communities. Furthermore, this research identifies latent constructs and indicates which observed variables load on or measure them. For the simulation, two complex data sets of questionnaires created by the Irish Commission for Energy Regulation (CER) were analyzed, demonstrating the influence of some exogenous variables on the items of the questionnaires. The results revealed that there is a relevant relationship between the social–economic and the behavioral factors and the observed variables. Furthermore, the models provided a good fit to the data, as measured by the performance indicators.

In this paper, we use attribute grammars as a formal approach for model checkers development. Our aim is to design an Alternating-Time Temporal Logic (ATL) model checker from a context-free grammar which generates the language of the ATL formulae. An attribute grammar may be informally defined as a context-free grammar which is extended with a set of attributes and a collection of semantic rules. We provide a formal definition for an attribute grammar used as input for Another Tool for Language Recognition (ANTLR) to generate an ATL model checker. The original implementation of the model-checking algorithm is based on Relational Databases and Web Services. Several database systems and Web Services technologies were used for evaluating the system performance in verification of large ATL models.

No abstract