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Titlebook: Networked Digital Technologies; 4th International Co Rachid Benlamri Conference proceedings 2012 Springer-Verlag Berlin Heidelberg 2012 MAN

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樓主: Consonant
21#
發(fā)表于 2025-3-25 05:27:41 | 只看該作者
Developing Casual Learning Games Using the Apache Pivot IIA Capabilitiesacilitators to fully incorporate games into the educational processes and how to efficiently deliver the games to the students. This paper introduces the Apache Pivot as a simplified environment for developing casual learning games. Two steps have been taken to demonstrate the simplicity of using th
22#
發(fā)表于 2025-3-25 08:31:08 | 只看該作者
Remote Robotic Laboratory Experiment Platform Based on Tele-programmingexperiments remotely through the internet. Remote control of experiments is gaining more importance in training and education. However, remote real-time training on instruments programming still have some unresolved problems such as error management. In this paper, a platform for training students o
23#
發(fā)表于 2025-3-25 13:26:41 | 只看該作者
24#
發(fā)表于 2025-3-25 19:49:31 | 只看該作者
Extended UML for the Development of Context-Aware ApplicationsSo, new application will be able to adapt its services with the change of context of use and satisfy all users’ preferences. In this work we present an UML extension for representing and modeling context because UML does not support all aspects of the context of use in an adequate manner. This exten
25#
發(fā)表于 2025-3-25 21:31:46 | 只看該作者
26#
發(fā)表于 2025-3-26 03:24:07 | 只看該作者
27#
發(fā)表于 2025-3-26 06:06:23 | 只看該作者
A Practical Method for Evaluating the Reliability of Telecommunication Network. Computing the reliability of networks is an NP-hard problem, which need efficient techniques to be evaluated. This paper presents a network reliability evaluation algorithm using Binary Decision Diagrams (BDD). The solution considers the 2-terminal reliability measure and proceeds first by enumera
28#
發(fā)表于 2025-3-26 11:04:38 | 只看該作者
Combining Classifiers for Spam Detectionmajor problem on the Internet and keeping users away from them becomes one of the most important research area. Indeed, spam filtering is used to prevent access to undesirable e-mails. In this paper we propose a spam detection system called “.” which uses machine learning to detect spam. “.” has the
29#
發(fā)表于 2025-3-26 14:59:20 | 只看該作者
30#
發(fā)表于 2025-3-26 20:10:02 | 只看該作者
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