5 resultados para Model driven development

em Digital Peer Publishing


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Open Source (OS) community offers numerous eLearning platforms of both types: Learning Management Systems (LMS) and Learning Content Systems (LCS). General purpose OS intermediaries such as SourceForge, ObjectWeb, Apache or specialized intermediaries like CampusSource reduce the cost to locate such eLearning platforms. Still, it is impossible to directly compare the functionalities of those OS software products without performing detailed testing on each product. Some articles available from eLearning Wikipedia show comparisons between eLearning platforms which can help, but at the end they barely serve as documentation which are becoming out of date quickly [1]. The absence of integration activities between OS eLearning platforms - which are sometimes quite similar in terms of functionalities and implementation technologies - is sometimes critical since most of the OS projects possess small financial and human resources. This paper shows a possible solution for these barriers of OS eLearning platforms. We propose the Model Driven Architecture (MDA) concept to capture functionalities and to identify similarities between available OS eLearning platforms. This contribution evolved from a fruitful discussion at the 2nd CampusSource Developer Conference at the University of Muenster (27th August 2004).

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wo methods for registering laser-scans of human heads and transforming them to a new semantically consistent topology defined by a user-provided template mesh are described. Both algorithms are stated within the Iterative Closest Point framework. The first method is based on finding landmark correspondences by iteratively registering the vicinity of a landmark with a re-weighted error function. Thin-plate spline interpolation is then used to deform the template mesh and finally the scan is resampled in the topology of the deformed template. The second algorithm employs a morphable shape model, which can be computed from a database of laser-scans using the first algorithm. It directly optimizes pose and shape of the morphable model. The use of the algorithm with PCA mixture models, where the shape is split up into regions each described by an individual subspace, is addressed. Mixture models require either blending or regularization strategies, both of which are described in detail. For both algorithms, strategies for filling in missing geometry for incomplete laser-scans are described. While an interpolation-based approach can be used to fill in small or smooth regions, the model-driven algorithm is capable of fitting a plausible complete head mesh to arbitrarily small geometry, which is known as "shape completion". The importance of regularization in the case of extreme shape completion is shown.

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This paper provides an insight to the development of a process model for the essential expansion of the automatic miniload warehouse. The model is based on the literature research and covers four phases of a warehouse expansion: the preparatory phase, the current state analysis, the design phase and the decision making phase. In addition to the literature research, the presented model is based on a reliable data set and can be applicable with a reasonable effort to ensure the informed decision on the warehouse layout. The model is addressed to users who are usually employees of logistics department, and is oriented on the improvement of the daily business organization combined with the warehouse expansion planning.

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Compliance with punctual delivery under the high pressure of costs can be implemented through the optimization of the in-house tool supply. Within the Transfer Project 13 of the Collaborative Research Centre 489 using the example of the forging industry, a mathematical model was developed which determines the minimum inventory of forging tools required for production, considering the tool appropriation delay.

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Simulation techniques are almost indispensable in the analysis of complex systems. Materials- and related information flow processes in logistics often possess such complexity. Further problem arise as the processes change over time and pose a Big Data problem as well. To cope with these issues adaptive simulations are more and more frequently used. This paper presents a few relevant advanced simulation models and intro-duces a novel model structure, which unifies modelling of geometrical relations and time processes. This way the process structure and their geometric relations can be handled in a well understandable and transparent way. Capabilities and applicability of the model is also presented via a demonstrational example.