Design and Implementation of a UML-Based Design Repository

Keller, Rudolf K.; Bédard, Jean‐François; Saint-Denis, Guy

doi:10.1007/3-540-45341-5_30

Cited by 6 publications

(3 citation statements)

References 14 publications

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“…It is not possible in the presented case. The reasoning based on ALE plots is inspired [64][65][66]. The proposed methods of ranking the influence of descriptors (amounts of CSRE components) on a dependent value (the compressive strength) through explainable artificial intelligence tools can be applied only if there is enough samples tested (several dozen are too little; 434 samples are just on the border).…”

Section: Discussionmentioning

confidence: 99%

Feature Importance of Stabilised Rammed Earth Components Affecting the Compressive Strength Calculated with Explainable Artificial Intelligence Tools

et al. 2020

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Cement-stabilized rammed earth (CSRE) is a sustainable construction material. The use of it allows for economizing on the cost of a structure. These two properties of CSRE are based on the fact that the soil used for the rammed mixture is usually dug close to the construction site, so it has random characteristics. That is the reason for the lack of widely accepted prescriptions for CSRE mixture, which could ascertain high enough compressive strength. Therefore, assessing which components of CSRE have the highest impact on its compressive strength becomes an important issue. There are three machine learning regression tools, i.e., artificial neural networks, decision tree, and random forest, used for predicting the compressive strength based on the relative content of CSRE composites (clay, silt, sand, gravel, cement, and water content). The database consisted of 434 samples of CSRE, which were prepared and crushed for testing purposes. Relatively low prediction errors of aforementioned models allowed for the use of explainable artificial intelligence tools (drop-out loss, mean squared error reduction, accumulated local effect) to rank the influence of the ingredients on the dependent variable—the compressive strength. Consistent results from all above-mentioned methods are discussed and compared to some statistical analysis of selected features. This innovative approach, helpful in designing the construction material is a solid base for reliable conclusions.

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Section: Discussionmentioning

confidence: 99%

Feature Importance of Stabilised Rammed Earth Components Affecting the Compressive Strength Calculated with Explainable Artificial Intelligence Tools

et al. 2020

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“…A number of implementations of repository systems that currently support UML also support XMI interchange of data, including the France Telecom model repository tool [1] and the SPOOL design repository [19]. These projects support extensible, standards based meta models.…”

Section: Transformationsmentioning

confidence: 99%

An Active Approach to Model Management for Evolving Information Systems

Gustavsson

Lings

Lundell

2003

Lecture Notes in Computer Science

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Abstract. It is desirable to be able to interchange design information between CASE tools. Such interchange facilitates cooperative development, helps in avoiding legacy problems when adopting new tools, and permits the use of different tools for different life-cycle activities. Exchanging model transformation information is particularly demanding in the context of cooperative maintenance of evolving systems. In this paper we suggest an approach using active transformation rules. We show how transformation rules can be expressed using a modest extension of the Object Constraint Language of the UML standard, and actively interpreted. The approach allows existing UML-based tools or repository systems to be readily extended to actively manage models in evolving information systems.

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“…The third case is as follows; when the adopted method is changed, the change is propagated to the model description that was developed with the older version of the method. Model management systems such as Coral [3] and UML repository systems [7,11] are only for meta models and only for products respectively. They do not consider the support for version control and change management sufficiently from method engineering context, i.e.…”

Section: Introductionmentioning

confidence: 99%

Configuration Management in a Method Engineering Context

Saeki

2006

Advanced Information Systems Engineering

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Method Engineering is the discipline for exploring techniques to build project-specific methods for information system development and Computer Aided Method Engineering (CAME) is a kind of computerized tool for supporting the processes to build them. In such method engineering environments, version control and change management for both model descriptions and method descriptions should be seamlessly combined. In addition, when the method being used is changed during a project, we should check whether the current version of a model is still consistent with the newer version of the adopted method. This paper proposes a technique to solve the issues on version control and change management in method engineering processes.

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Design and Implementation of a UML-Based Design Repository

Cited by 6 publications

References 14 publications

Feature Importance of Stabilised Rammed Earth Components Affecting the Compressive Strength Calculated with Explainable Artificial Intelligence Tools

Feature Importance of Stabilised Rammed Earth Components Affecting the Compressive Strength Calculated with Explainable Artificial Intelligence Tools

An Active Approach to Model Management for Evolving Information Systems

Configuration Management in a Method Engineering Context

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