Protocol Modelling

McNeile, Ashley T.; Simons, Nicholas

doi:10.1007/978-3-319-21912-7_7

Cited by 5 publications

(7 citation statements)

References 2 publications

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“…These values are given in Table X. With these B jk values, and the a n coefficients from our fit (via the direct method), we find B 0 = 0.00073(89) , B + = 0.0210 (54) .…”

Section: Appendix C: Tests Of Unitarity Boundsmentioning

confidence: 75%

Bs→Dsℓν form factors for the full q
McLean
¹
,
Davies
²
,
Koponen
³

et al. 2020
Phys. Rev. D
82
9
92
0
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We present a lattice QCD determination of the Bs → Ds ν scalar and vector form factors over the full physical range of momentum transfer. The result is derived from correlation functions computed using the Highly Improved Staggered Quark (HISQ) formalism, on the second generation MILC gluon ensembles accounting for up, down, strange and charm contributions from the sea. We calculate correlation functions for three lattice spacing values and an array of unphysically light b-quark masses, and extrapolate to the physical value. Using the HISQ formalism for all quarks means that the lattice current coupling to the W can be renormalized non-perturbatively, giving a result free from perturbative matching errors for the first time. Our results are in agreement with, and more accurate than, previous determinations of these form factors. From the form factors we also determine the ratio of branching fractions that is sensitive to violation of lepton universality: R(Ds) = B(Bs → Dsτ ντ )/B(Bs → Ds ν l ), where is an electron or a muon. We find R(Ds) = 0.2987(46), which is also more accurate than previous lattice QCD results. Combined with a future measurement of R(Ds), this could supply a new test of the Standard Model. We also compare the dependence on heavy quark mass of our form factors to expectations from Heavy Quark Effective Theory.

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“…These values are given in Table X. With these B jk values, and the a n coefficients from our fit (via the direct method), we find B 0 = 0.00073(89) , B + = 0.0210 (54) .…”

Section: Appendix C: Tests Of Unitarity Boundsmentioning

confidence: 75%

Bs→Dsℓν form factors for the full q
McLean
¹
,
Davies
²
,
Koponen
³

et al. 2020
Phys. Rev. D
82
9
92
0
View full text Add to dashboard Cite

show abstract

“…The bottom left shows the result of composing SD1 with SD2 using the state diagram composition operator defined by the HiLA appoach [44]. The bottom right shows the result of composing the same state diagrams using the state diagram composition operator defined as part of the Protocol Modeling approach (PM) [30], which is in turn inspired by the CSP parallel composition operator .…”

Section: Need For Different Homogeneous Composition Operators For Stamentioning

confidence: 99%

“…State Diagram Composition: RAM allows a software designer to specify operation invocation protocols for each design class using state views [2], which are a variant of protocol state diagrams called protocol models [30]. A state view comprises a set of states and a set of named transitions that stand for the operations that the class declares.…”

Section: Examples Of Behavioral Weaversmentioning

confidence: 99%

A unifying framework for homogeneous model composition

et al. 2019

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The growing use of models for separating concerns in complex systems has lead to a proliferation of model composition operators. These composition operators have traditionally been defined from scratch following various approaches differing in formality, level of detail, chosen paradigm, and styles. Due to the lack of proper foundations for defining model composition (concepts, abstractions, or frameworks), it is difficult to compare or reuse composition operators. In this paper, we stipulate the existence of a unifying framework that reduces all structural composition operators to structural merging, and all composition operators acting on discrete behaviors to event scheduling. We provide convincing evidence of this hypothesis by discussing how structural and behavioral homogeneous model composition operators (i.e., weavers) can be mapped onto this framework. Based on this discussion, we propose a conceptual model of the framework, and identify a set of research challenges, which, if addressed, lead to the realization of this framework to support rigorous and efficient engineering of model composition operators for homogeneous and eventually heterogeneous modeling languages.

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“…By accepting or refusing this event the protocol model communicates with the environment. This communication is simulated in Modelscope tool supporting Protocol Modelling (McNeile and Simons, 2005).…”

Section: The Protocol Model Of the Program For Iaptmentioning

confidence: 99%

“…As a protocol model is a combination of process model and data model, it contains useful procedures for communication of protocol machines with data and advanced procedures for derivation of states of one protocol machine from the states of others. These advanced protocol modelling operators are supported with the Modelscope tool (McNeile and Simons, 2005). The model is executed and tested.…”

Section: Related Work and Conclusionmentioning

confidence: 99%

Modelling and Validation of KPIs

Roubtsova

Michell

2013

Proceedings of the Third International Symposium on Proceedings of the Third International Symposium on Business Modeling and S

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Competition for funding between organizations attracts attention to their Key Performance Indicators (KPIs). KPIs are usually designed with a top-down approach as families of measures for a group of business units and often do not take into account the difference in goals and business processes of organizations at the strategic, tactical and operational level. This results in unreliable, inefficient and sometimes inconsistent KPIs. Validation of KPI properties is typically postponed until the KPI is implemented, and databases are populated with values. The reason is the absence of intuitive and simple methods for KPI modelling that relate the strategic and tactical models and executable operational models. We propose such a method for KPI modelling and validation of their properties. Our method combines ideas of goal, conceptual and executable process modelling. Models at all levels are derived from KPI definitions. The conceptual modelling techniques are used to relate the strategic and tactical models. The synchronous semantics of protocol modelling is used to relate the tactical and the operational models. The executable operational and tactical models enable derivation the KPI values, testing KPIs against the desired properties and identification of ambiguities in KPI definitions that need to be resolved to improve KPIs.

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Protocol Modelling

Cited by 5 publications

References 2 publications

Bs→Dsℓν form factors for the full q
McLean
¹
,
Davies
²
,
Koponen
³

et al. 2020
Phys. Rev. D
82
9
92
0
View full text Add to dashboard Cite

Bs→Dsℓν form factors for the full q
McLean
¹
,
Davies
²
,
Koponen
³

et al. 2020
Phys. Rev. D
82
9
92
0
View full text Add to dashboard Cite

A unifying framework for homogeneous model composition

Modelling and Validation of KPIs

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Protocol Modelling

Cited by 5 publications

References 2 publications

Bs→Dsℓν form factors for the full qMcLean1, Davies2, Koponen3 et al. 2020Phys. Rev. D829920View full textAdd to dashboardCite

Bs→Dsℓν form factors for the full qMcLean1, Davies2, Koponen3 et al. 2020Phys. Rev. D829920View full textAdd to dashboardCite

A unifying framework for homogeneous model composition

Modelling and Validation of KPIs

Contact Info

Product

Resources

About

Bs→Dsℓν form factors for the full q
McLean
¹
,
Davies
²
,
Koponen
³

et al. 2020
Phys. Rev. D
82
9
92
0
View full text Add to dashboard Cite

Bs→Dsℓν form factors for the full q
McLean
¹
,
Davies
²
,
Koponen
³

et al. 2020
Phys. Rev. D
82
9
92
0
View full text Add to dashboard Cite