Collaborative Verification-Driven Engineering of Hybrid Systems

Hybrid systems with both discrete and continuous dynamics are an important model for real-world cyber-physical systems. The key challenge is to ensure their correct functioning w.r.t. safety requirements. Promising techniques to ensure safety seem to be model-driven engineering to develop hybrid systems in a well-defined and traceable manner, and formal verification to prove their correctness. Their combination forms the vision of verification-driven engineering. Often, hybrid systems are rather complex in that they require expertise from many domains (e.g., robotics, control systems, computer science, software engineering, and mechanical engineering). Moreover, despite the remarkable progress in automating formal verification of hybrid systems, the construction of proofs of complex systems often requires nontrivial human guidance, since hybrid systems verification tools solve undecidable problems. It is, thus, not uncommon for development and verification teams to consist of many players with diverse expertise. This paper introduces a verification-driven engineering toolset that extends our previous work on hybrid and arithmetic verification with tools for (i) graphical (UML) and textual modeling of hybrid systems, (ii) exchanging and comparing models and proofs, and (iii) managing verification tasks. This toolset makes it easier to tackle large-scale verification tasks

Abstracts of theses and related literature indicating current trends in arithmetic for the academically talented elementary school child written between 1957 and 1961

Thesis (Ed.M.)--Boston Universit

Reading and arithmetic in adolescents with autism spectrum disorders: Peaks and dips in attainment

In describing academic attainment in autism spectrum disorders (ASD), results are typically reported at the group mean level. This may mask subgroups of individuals for whom academic achievement is incommensurate with intellectual ability. The authors tested the IQ, literacy, and mathematical abilities of a large group (N = 100) of adolescents (14–16 years old) with ASD. Seventy-three percent of the sample had at least one area of literacy or mathematical achievement that was highly discrepant (approximately 14 standard score points) from full-scale IQ (FSIQ). The authors focused on four subgroups with either word reading (“Reading Peak” and “Reading Dip”) or arithmetic (“Arithmetic Peak” and “Arithmetic Dip”) higher or lower than FSIQ. These subgroups were largely mutually exclusive and were characterized by distinct intellectual profiles. The largest was the “Arithmetic Peak” subgroup of participants, who presented with average intellectual ability alongside superior arithmetic skills and who were predominantly in a mainstream educational setting. Overall, the most pervasive profile was discrepantly poor reading comprehension, which associated with severity of social and communication difficulties. The high rate of uneven academic attainment in ASD has implications for educational practice

A Vision of Collaborative Verification-Driven Engineering of Hybrid Systems

Abstract. Hybrid systems with both discrete and continuous dynamics are an important model for real-world physical systems. The key challenge is how to ensure their correct functioning w.r.t. safety requirements. Promising techniques to ensure safety seem to be model-driven engineering to develop hybrid systems in a well-defined and traceable manner, and formal verification to prove their correctness. Their combination forms the vision of verification-driven engineering. Despite the remarkable progress in automating formal verification of hybrid systems, the construction of proofs of complex systems often requires significant human guidance, since hybrid systems verification tools solve undecidable problems. It is thus not uncommon for verification teams to consist of many players with diverse expertise. This paper introduces a verification-driven engineering toolset that extends our previous work on hybrid and arithmetic verification with tools for (i) modeling hybrid systems, (ii) exchanging and comparing models and proofs, and (iii) managing verification tasks. This toolset makes it easier to tackle large-scale verification tasks.

From Euclidean Geometry to Knots and Nets

This document is the Accepted Manuscript of an article accepted for publication in Synthese. Under embargo until 19 September 2018. The final publication is available at Springer via https://doi.org/10.1007/s11229-017-1558-x.This paper assumes the success of arguments against the view that informal mathematical proofs secure rational conviction in virtue of their relations with corresponding formal derivations. This assumption entails a need for an alternative account of the logic of informal mathematical proofs. Following examination of case studies by Manders, De Toffoli and Giardino, Leitgeb, Feferman and others, this paper proposes a framework for analysing those informal proofs that appeal to the perception or modification of diagrams or to the inspection or imaginative manipulation of mental models of mathematical phenomena. Proofs relying on diagrams can be rigorous if (a) it is easy to draw a diagram that shares or otherwise indicates the structure of the mathematical object, (b) the information thus displayed is not metrical and (c) it is possible to put the inferences into systematic mathematical relation with other mathematical inferential practices. Proofs that appeal to mental models can be rigorous if the mental models can be externalised as diagrammatic practice that satisfies these three conditions.Peer reviewe

Inter-individual cognitive variability in children with Asperger's syndrome

Multiple studies have tried to establish the distinctive profile of individuals with Asperger's syndrome (AS). However, recent reports suggest that adults with AS feature heterogeneous cognitive profiles. The present study explores inter-individual variability in children with AS through group comparison and multiple case series analysis. All participants completed an extended battery including measures of fluid and crystallized intelligence, executive functions, theory of mind, and classical neuropsychological tests. Significant group differences were found in theory of mind and other domains related to global information processing. However, the AS group showed high inter-individual variability (both sub- and supra-normal performance) on most cognitive tasks. Furthermore, high fluid intelligence correlated with less general cognitive impairment, high cognitive flexibility, and speed of motor processing. In light of these findings, we propose that children with AS are characterized by a distinct, uneven pattern of cognitive strengths and weaknesses.Fil: González Gadea, María Luz. Universidad Diego Portales; Chile. Universidad Favaloro; Argentina. Instituto de Neurología Cognitiva; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Tripicchio, Paula. Instituto de Neurología Cognitiva; Argentina. Universidad Favaloro; ArgentinaFil: Rattazzi del Carril, Alexia. Instituto de Neurología Cognitiva; Argentina. Universidad Favaloro; ArgentinaFil: Báez Buitrago, Sandra Jimena. Universidad Favaloro; Argentina. Universidad Diego Portales; Chile. Universidad Catolica Argentina; Argentina. Instituto de Neurología Cognitiva; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Marino, Julián Carlos. Universidad Nacional de Córdoba. Facultad de Psicología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Roca, María. Universidad Favaloro; Argentina. Instituto de Neurología Cognitiva; Argentina. Universidad Diego Portales; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Manes, Facundo Francisco. Instituto de Neurología Cognitiva; Argentina. Universidad Favaloro; Argentina. Universidad Diego Portales; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Centre of Excellence in Cognition and its Disorders; AustriaFil: Ibanez Barassi, Agustin Mariano. Instituto de Neurología Cognitiva; Argentina. Universidad Favaloro; Argentina. Universidad Diego Portales; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Centre of Excellence in Cognition and its Disorders; Austria. Universidad Autonoma del Caribe; Colombi