Redirigiendo al acceso original de articulo en 16 segundos...
ARTÍCULO
TITULO

An Improved Model Facet Method to Support EA Alignment

Jonathan Pepin    
Pascal André    
Christian Attiogbé    
Erwan Breton    

Resumen

Information System evolution requires a well-structured Enterprise Architecture and its rigorous management. The alignment of the elements in the architecture according to various abstraction layers may contribute to the management but appropriate tools are needed. We propose improvements to the Facet technique and we develop accompanying tools to master the difficulties of the alignment of the models used to structure an Enterprise Architecture. This technique has been experimented on many real life cases to demonstrate the effectiveness of our EA alignment method. The tools are already integrated in the Eclipse EMF Facet project.

 Artículos similares

       
 
Anthony A. Amori, Olufemi P. Abimbola, Trenton E. Franz, Daran Rudnick, Javed Iqbal and Haishun Yang    
Model calibration is essential for acceptable model performance and applications. The Hybrid-Maize model, developed at the University of Nebraska-Lincoln, is a process-based crop simulation model that simulates maize growth as a function of crop and fiel... ver más
Revista: Water

 
Tianao Qin, Ruixin Chen, Rufu Qin and Yang Yu    
Time series prediction is an effective tool for marine scientific research. The Hierarchical Temporal Memory (HTM) model has advantages over traditional recurrent neural network (RNN)-based models due to its online learning and prediction capabilities. G... ver más

 
Yanqi Wang, Xinyan Qin, Wenxing Jia, Jin Lei, Dexin Wang, Tianming Feng, Yujie Zeng and Jie Song    
In order to improve the flight efficiency of a flying?walking power transmission line inspection robot (FPTLIR) during flight missions, an accurate energy consumption model is constructed, and a multiobjective optimization approach using the improved NSG... ver más
Revista: Applied Sciences

 
Mingxin Zou, Yanqing Zhou, Xinhua Jiang, Julin Gao, Xiaofang Yu and Xuelei Ma    
Field manual labor behavior recognition is an important task that applies deep learning algorithms to industrial equipment for capturing and analyzing people?s behavior during field labor. In this study, we propose a field manual labor behavior recogniti... ver más
Revista: Applied Sciences

 
Yuntao Shi, Qi Luo, Meng Zhou, Wei Guo, Jie Li, Shuqin Li and Yu Ding    
Objects thrown from tall buildings in communities are characterized by their small size, inconspicuous features, and high speed. Existing algorithms for detecting such objects face challenges, including excessive parameters, overly complex models that ar... ver más
Revista: Information