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Introduction to the Software Engineering and Formal Methods 2013 special issue
2015
Journal of Software and Systems Modeling
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We received support from the SEFM Steering Committee in organizing the conference and, in particular, its Chair, Professor Antonio Cerone. ...
inference of units of measure for physical quantities. ...
In "Inferring Physical Units in Formal Models", Sebastian Krings and Michael Leuschel present an extension to the B, Event-B and TLA + formal specification languages to support the analysis and partial ...
doi:10.1007/s10270-015-0467-z
fatcat:4kx5rptrhzgzdoanvphkhiwoza
Cyber-Physical Specification Mismatches
[article]
2018
arXiv
pre-print
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Dynamic specifications in the form of candidate invariants of both the software and physical components are identified using dynamic analysis (executing and/or simulating the system implementation or model ...
invariant inference tool, which has been extensively applied to software systems. ...
Any opinions, ndings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily re ect the views of AFRL, AFOSR, or NSF. ...
arXiv:1806.09224v1
fatcat:bdoizxxf2zajlbqdu42yli2zgm
From Requirements to Models: Feedback Generation as a Result of Formalization
[chapter]
2011
Lecture Notes in Computer Science
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This causes problems during modeling or programming. The aim of the presented paper is to make deficiencies in behavior specifications apparent in the early project stage. ...
The basic idea is to model the required system behavior and to generate feedback for human analysts, based on the deficiencies of the resulting models. ...
specification into a formal model. ...
doi:10.1007/978-3-642-21640-4_9
fatcat:wr7dooz4g5f4nb35reyoaii7qe
Improved circuit model for left-handed lines loaded with split ring resonators
2008
Applied Physics Letters
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The weakness relies on the physical interpretation of the elements of that model. ...
On the other hand, we have inverted Eqs. ͑6͒ and ͑7͒ in order to obtain the parameters of the model of Fig. 3͑a͒ , and they show a very good agreement with those parameters inferred in the structure without ...
doi:10.1063/1.2839600
fatcat:rwqcke4cb5di3plgrwqesvsubq
Scientific modelling with diagrams
2019
Synthese
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Diagrams can serve as representational models in scientific research, yet important questions remain about how they do so. ...
models. ...
Acknowledgements An earlier version of this paper was presented at two workshops in 2016 ("Many Methods, One Biology?", Munich, and "Representing Scientific Results", Kassel). ...
doi:10.1007/s11229-019-02239-0
fatcat:m7v3wpqzt5fnpfpi6mwirqbqei
Learning Units-of-Measure from Scientific Code
2019
2019 IEEE/ACM 14th International Workshop on Software Engineering for Science (SE4Science)
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One core feature provides units-of-measure verification (dimensional analysis) of programs, where users partially annotate programs with units-of-measure from which our tool checks consistency and infers ...
However, many users find it onerous to provide units-of-measure information for existing code, even in part. ...
Since scientific models usually handle numerical quantities with physical meaning, a helpful lightweight technique is to statically verify the consistency of units-of-measure in computations. ...
doi:10.1109/se4science.2019.00013
dblp:conf/icse/DanishABRO19
fatcat:46cylbgcdjbxxo5hktpzzrn3fq
Why Can the Brain (and Not a Computer) Make Sense of the Liar Paradox?
2021
Frontiers in Ecology and Evolution
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Finally, we show that the representation of logical inconsistencies in the Strange Loop Model leads to causal incongruence between brain subsystems in Integrated Information Theory. ...
In contrast, the human mind can understand self-referential statements without necessitating physically impossible brain states. Why can the brain make sense of self-reference? ...
In this way, if we want to model deductive inferences as processes carried out by a physical systems such as the brain which evolves in time, we see that the contradictions appear not directly, but spread ...
doi:10.3389/fevo.2021.802300
fatcat:zi5efifdtrcsfc6gg346eqwz5a
STRUCTURED CONNECTIONIST MODELS OF LANGUAGE, COGNITION AND ACTION
2005
Modeling Language, Cognition and Action
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We focus in this paper on the computational level and explore the role of embodied representations and simulative inference in language understanding. a Previously the L 0 group; see also Feldman et al ...
The Neural Theory of Language project aims to build structured connectionist models of language and cognition consistent with constraints from all domains and at all levels. ...
These demonstrate how embodied representations facilitate inference in both concrete physical and more abstract domains. ...
doi:10.1142/9789812701886_0005
fatcat:vegudmzdfrekra6drhdz2xucfu
Diagrams as Physical Models
[chapter]
2006
Lecture Notes in Computer Science
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One line of research in diagrammatic reasoning is that diagrams, rather then being models, are formal representations with specialized rules of inference that generate new diagrams. ...
When the physical model is prototypical, it supports the inference of certain other sentences for which it provides a model as well. ...
plausible subtasks may be hypothesized for formal inference, and providing a model of the premises from which consequents can be inferred and asserted. ...
doi:10.1007/11783183_28
fatcat:7mjfmbwsebeyhfhxd47b4bvzka
Logicist statistics. I. Models and modeling
1998
Statistical Science
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Arguments are presented to support increased emphasis on logical aspects of formal methods of analysis, depending on probability in the sense of R. A. Fisher. ...
Contexts in which these ideas are intended to apply are discussed via three major examples. ...
ACKNOWLEDGMENT Supported in part by NSF Grant DMS-94-04396 to Harvard University and through the Geophysical Statistics Project at the National Center for Atmospheric Research. ...
doi:10.1214/ss/1028905887
fatcat:oalaybalufht5cmapryhfgzgte
Formalizing Tag-Based Metadata With the Brick Ontology
2020
Frontiers in Built Environment
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To address these issues, we present the design and implementation of the Brick+ ontology, a drop-in replacement for Brick with clear formal semantics that enables the inference of a valid Brick model from ...
an informal Haystack model, and demonstrate this inference across five Haystack models. ...
of six centers in JUMP, a Semiconductor Research Corporation (SRC) program sponsored by DARPA. ...
doi:10.3389/fbuil.2020.558034
fatcat:wcox4ktt4bf3vamxyh7e6ajevq
Acquisition of gradual knowledge
[chapter]
1993
Lecture Notes in Computer Science
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At the symbol level, different representations and implementations of topoi can be proposed and topoi can be formalized through several qualitative physics formalisms. 1 The term "topoi" was chosen as ...
Topoi are gradual inference rules, often used by experts in several problem classes: they can be exploited at various phases of a knowledge-based system life cycle. ...
described through qualitative physics formalisms, while our work aims at formalizing and representing the topoi elicited from the expert, through qualitative physics formalisms, at the symbol level. ...
doi:10.1007/3-540-57253-8_65
fatcat:7b4t4hbqhzh67njucb3gslh7ky
Experiments and Observational Studies
[chapter]
2008
Studying Human Populations
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concept in causal inference. ...
as believing that the thinkers quoted in Section 2 had Neyman's formalization in mind prior to 1923. ...
doi:10.1007/978-0-387-73251-0_7
fatcat:fvznkm57nbcg5kidwnncbadqqi
Knowledge acquisition by conceptual modelling
1992
Applied Mathematics Letters
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The Inferential Model and the implicit Inferential Modelling Technique are described and applied to rmalyse expertise in the legal domain of negligence. ...
We present a classification of knowledge types which is useful for acquisition and analysis of knowledge before it is formally represented in an expert system. ...
We believe explicit categorizing of knowledge units and clarifying characteristics of the domain concepts and relations is fundamental to conceptual modelling of expertise for formal representation. ...
doi:10.1016/0893-9659(92)90027-7
fatcat:fxelt6fa2zhdjou7if5ibwchqu
Combining Knowledge and Deep Learning for Prognostics and Health Management
2022
Proceedings of the European Conference of the Prognostics and Health Management Society (PHME)
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Before the broad success of deep learning machine faults were often classified using domain expert knowledge based on experience and physical models. ...
In the recent past deep learning approaches have achieved remarkable results in the area of Prognostics and Health Management (PHM). ...
In comparison to work in Sec. 2, where mainly physical knowledge was used to improve DL, the focus will be on additionally integrating symbolic knowledge for the union of different models and formalizing ...
doi:10.36001/phme.2022.v7i1.3302
fatcat:5q2nxgkjnnc3jayledpk4kuexi
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