Towards a model-driven engineering approach for the assessment of non-functional properties using multi-formalism

Bernardi, Simona; Marrone, S.; Merseguer, José; Nardone, Roberto; Vittorini, Valeria

doi:10.1007/s10270-018-0663-8

Cited by 8 publications

(6 citation statements)

References 41 publications

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“…On the temporal level, the major limitation of the fusion between EEG and fMRI is the difference in their temporal resolutions. From the perspective of temporal-spatial information sharing and fusion, scholars are willing to put more emphasis on the integration of multimodal temporal-spatial information, in which the model-driven and nonmodel-driven are the two most frequently used data fusion methods [17][18][19]. e data collection of EEG and fMRI neuroimaging technologies is shown in Figure 1.…”

Section: Temporal and Spatial Data Mining Of Human Brain Based On Foca Under Eeg-fmri Fusionmentioning

confidence: 99%

[Retracted] Construction of a Multimodal Neuroimaging Data Fusion System and Evaluation of Mental Fatigue Using Nonlinear Analysis

Chen

Lai

2021

Complexity

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The purpose of this research is to explore the optimization and fusion application of multimodal neuroimaging technology and analyze the evaluation method of human brain fatigue based on multimodal neuroimaging technology. Based on electroencephalogram (EEG) and fMRI (functional magnetic resonance imaging), the four-dimensional consistency of local neural activities (FOCA) and local multimodal serial analysis (LMSA) are first introduced to fuse EEG and fMRI organically. Second, the eigenspace maximal information canonical correlation analysis (emiCCA) is introduced to construct the multimodal neuroimaging data fusion system. Finally, how the brain function network is constructed is introduced. Based on the binary and the weighted brain function networks, the relationship between the human brain fatigue and the brain function network is evaluated by calculating the fractal dimension. Results demonstrate that FOCA performs well in temporal and spatial consistency indexes, and the mean level and standard deviation in the case of temporal and spatial consistency are approximately 0.45. The effect of LMSA indexes is significantly better than generalized linear models (GLMs). Under different signal-to-noise ratios (SNRs), the regression coefficient based on LMSA is much larger than the GLM estimate; the corresponding significance level is p < 0.05 ; and the maximum value of the regression coefficient appears near 0.2. In the data fusion system, the time-space matching has good results under the time accuracy based on EEG and the space accuracy based on fMRI, with the time accuracy above 88% and the space accuracy above 89%. The fractal dimension analysis based on the brain function network reveals that the weighted brain function network is more sensitive to mental fatigue. The state of human brain fatigue will make the brain function network more complicated. The fractal dimension with more network edges is around 2.2, while the fractal dimension with fewer network edges is around 1.6. The proposed data analysis and fusion system have great application potential and propose a new idea for analyzing human brain fatigue and brain aging.

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Section: Temporal and Spatial Data Mining Of Human Brain Based On Foca Under Eeg-fmri Fusionmentioning

confidence: 99%

[Retracted] Construction of a Multimodal Neuroimaging Data Fusion System and Evaluation of Mental Fatigue Using Nonlinear Analysis

Chen

Lai

2021

Complexity

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“…There are other approaches that propose different solutions for evaluating nonfunctional properties using models, such as the one by Bernardi et al, 43 who propose the assessment of nonfunctional properties using multiformalism approaches, but they do not address self-adaptive systems. In particular, they are proposing an integrated model to combine performance and reliability models, which allows the construction of models for performance analysis, and automated construction of multiformalism models with less effort.…”

Section: Related Workmentioning

confidence: 99%

A procedural and flexible approach for specification, modeling, definition, and analysis for self‐adaptive systems

2021

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An adaptive system can modify its settings at runtime as a response to changes in its operational environment. To analyse this kind of systems at design time is a difficult task since it requires considering the system together with the adaptation operations, and taking into account how such adaptations act on the system. In order to use simulation-based techniques for the analysis of such systems, we not only need precise executable models of the systems to be analyzed, but also to capture the semantics of their adaptation mechanisms. Given the wide range and flexibility of adaptation operations, we need ways to allow the definition of new operations. We present a flexible approach for the definition and simulation-based analysis in design-time of adaptive component-based systems. Our approach combines an extension of the Palladio component model in e-Motions, a model of the adaptation mechanisms, and elastic requirements specification using the SYBL language. From the model of the system, its adaptation mechanisms, and its requirements, an executable Maude specification is generated for simulation. The application of the approach is illustrated on a use case that comprises some components and adaptations rules. The example is then analyzed using simulations. It is also shown that it is indeed possible to define additional metrics, specify adaptation requirements and rules which conduct simulations of the models in a more flexible way, and that the results of the simulation performed from these definitions can be used to carry on a valuable predictive performance analysis. K E Y W O R D Sadaptation specification, design-time analysis, modeling, self-adaptive behavior, self-adaptive models INTRODUCTIONSoftware architecture has become an essential element in building consistent systems as the size and complexity of software systems have increased. The necessity to take into account not only the overall structure of the system itself but also the allocation, functionality, and communication of the software components became a challenge for building

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“…More recently, Bernardi et al [36] defined an approach to integrate different model generation chains. They assume the existence of multiple, independent, transformation chains, each one directly generating a formal model (e.g., SPNs) from a high-level model (e.g., UML).…”

Section: Model-driven Approachesmentioning

confidence: 99%

“…Composition rules become part of model libraries, and only one single model transformation/composition algorithm is defined, which is the same for every library of model templates. Essentially, we use a horizontal intermediate model (between the design-level representation and formal models), whereas Bernardi et al [36] uses a vertical intermediate model (between different transformation chains).…”

Section: Model-driven Approachesmentioning

confidence: 99%

A Template-Based Methodology for the Specification and Automated Composition of Performability Models

2020

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Dependability and performance analysis of modern systems is facing great challenges: their scale is growing, they are becoming massively distributed, interconnected, and evolving. Such complexity makes model-based assessment a difficult and time-consuming task. For the evaluation of large systems, reusable submodels are typically adopted as an effective way to address the complexity and to improve the maintainability of models. When using state-based models, a common approach is to define libraries of generic submodels, and then compose concrete instances by state sharing, following predefined "patterns" that depend on the class of systems being modeled. However, such composition patterns are rarely formalized, or not even documented at all. In this paper, we address this problem using a model-driven approach, which combines a language to specify reusable submodels and composition patterns, and an automated composition algorithm. Clearly defining libraries of reusable submodels, together with patterns for their composition, allows complex models to be automatically assembled, based on a high-level description of the scenario to be evaluated. This paper provides a solution to this problem focusing on: formally defining the concept of model templates, defining a specification language for model templates, defining an automated instantiation and composition algorithm, and applying the approach to a case study of a large-scale distributed system.

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Towards a model-driven engineering approach for the assessment of non-functional properties using multi-formalism

Cited by 8 publications

References 41 publications

[Retracted] Construction of a Multimodal Neuroimaging Data Fusion System and Evaluation of Mental Fatigue Using Nonlinear Analysis

[Retracted] Construction of a Multimodal Neuroimaging Data Fusion System and Evaluation of Mental Fatigue Using Nonlinear Analysis

A procedural and flexible approach for specification, modeling, definition, and analysis for self‐adaptive systems

A Template-Based Methodology for the Specification and Automated Composition of Performability Models

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