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Titlebook: Digital Information and Communication Technology and Its Applications; International Confer Hocine Cherifi,Jasni Mohamad Zain,Eyas El-Qawas

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Grundlagen und rechtlicher Rahmen,ding to evolutions of the product or the usage requirements. The approach is being proofed in validating high-class sensor prototypes for the automotive industry, which in particular illustrates how operational issues related to the different level of abstraction between textual specifications and effective test routines can be solved.
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https://doi.org/10.1007/978-3-642-01073-6se independent models. This separates all the concerns from the business logic and provides a proper understanding of different modules that are to be developed well before the start of the coding phase thereby reducing the burden of artifact design from the developers.
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Grundlagen und rechtlicher Rahmen,fferent data distribution. A qualitative comparison of these methods has been performed in the processing of gastric electrical activity (GEA) signal and classifying GEA types to discriminate two GEA types: normal and FGD. The GEA signals are first decomposed into components in different sub-bands using discrete wavelet transformation.
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https://doi.org/10.1007/978-3-8350-9387-4llocating dynamic data spaces for other processes in other machines. In fact, the increasing use of high-bandwidth and low-latency networks provides the possibility to use the distributed memory as an alternative to disk.
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Measuring Understandability of Aspect-Oriented Codeave to put their effort on to recognizing the logical concept of the components”, this paper proposes seven metrics for evaluating understandability of aspect-oriented code using different levels of dependence graphs. The metrics are applied to two versions of aspect-oriented programs to give an illustration.
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Aspect Oriented and Component Based Model Driven Architecturese independent models. This separates all the concerns from the business logic and provides a proper understanding of different modules that are to be developed well before the start of the coding phase thereby reducing the burden of artifact design from the developers.
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A Comparative Analysis and Simulation of Semicompetitive Neural Networks in Detecting the Functionalfferent data distribution. A qualitative comparison of these methods has been performed in the processing of gastric electrical activity (GEA) signal and classifying GEA types to discriminate two GEA types: normal and FGD. The GEA signals are first decomposed into components in different sub-bands using discrete wavelet transformation.
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