General mixed-data model: Extension of general location and grouped continuous models

2007 ◽  
Vol 35 (4) ◽  
pp. 533-548 ◽  
Author(s):  
Alexander R. De LEON ◽  
K. C. Carriègre
Keyword(s):  
Data Model ◽  
Mixed Data ◽  
Continuous Models ◽  
Model Extension

scholarly journals Mixed-data-model heterogeneous compilation and OpenMP offloading

2020 ◽  
Author(s):  
Andreas Kurth ◽  
Koen Wolters ◽  
Björn Forsberg ◽  
Alessandro Capotondi ◽  
Andrea Marongiu ◽  
...  
Keyword(s):  
Data Model ◽  
Mixed Data

Visual Information Model of Car-Body Welding and Assembly Process

Manufacturing ◽  
2003 ◽  
Author(s):  
Bo Sui ◽  
Dong Du ◽  
Baohua Chang ◽  
Feng Zhai ◽  
Li Wang
Keyword(s):  
Data Model ◽  
Visual Information ◽  
Process Analysis ◽  
Welding Process ◽  
Information Model ◽  
Mixed Data ◽  
Assembly Process ◽  
Process Plan ◽  
Analysis And Design ◽  
Car Body

The complexity of car-body welding and assembly process makes it difficult for engineers to design and analyze the process parameters. Therefore, a tree-relation mixed data model, based on the characteristics of car-body assemply process, is put forward to represent the welding and assembly process. By integrating this data model with CAD/CAM model and 3d graphic simulation platform, a visual information model is built up. A case study is performed on the visualization of car-door welding and assembly process plan using this information model. The result shows that the model is able to represent the process plan of welding and assembly process visually and integrally. The model can be used for auto-body design, welding-process analysis and design, process information management, quality control and personalized selling.

Information Processing Based on Mixed - Classical and Fuzzy - Data Models

2001 ◽  
Vol 5 (1) ◽  
pp. 44-50
Author(s):  
Orsolya Takács ◽  
◽  
Annamária R. Várkonyi-Kóczy
Keyword(s):  
Information Processing ◽  
Data Model ◽  
Uncertain Data ◽  
Data Models ◽  
Mixed Data ◽  
Fuzzy Data ◽  
Classical Probability ◽  
Mixed Use ◽  
Achievable Accuracy ◽  
Data Processing Methods

The model used to represent information during information processing could affect achievable accuracy and could determine the usability of different calculation methods. The data model must also be able to represent uncertainty and inaccuracy both of input data and results. The two most popular data models for representation of uncertain data is the "classical", probability based, and the recently introduced fuzzy data models. Both data models have their own calculation and data processing methods, but with the increasing complexity of calculation problems, a method for the mixed use of these data models is be needed. This paper deals with possible solutions for information processing based on mixed data models and examines the different conversion methods between fuzzy and probability theory based data models.

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