By Rempt B.
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Ambient intelligence is the imaginative and prescient of a expertise that may turn into invisibly embedded in our average atmosphere, current each time we want it, enabled by way of easy and easy interactions, attuned to all our senses, adaptive to clients and context-sensitive, and self sustaining. top of the range details entry and customized content material has to be to be had to every body, at any place, and at any time.
Cross-Word Modeling for Arabic Speech acceptance makes use of phonological ideas in an effort to version the cross-word challenge, a merging of adjoining phrases in speech brought on by non-stop speech, to augment the functionality of constant speech acceptance platforms. the writer goals to supply an realizing of the cross-word challenge and the way it may be kept away from, in particular targeting Arabic phonology utilizing an HHM-based classifier.
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This publication constitutes the refereed complaints of the second one foreign convention on Augmented and digital fact, AVR 2015, held in Lecce, Italy, in September 2015. The 32 papers and eight brief papers awarded have been rigorously reviewed and chosen from eighty two submissions. The SALENTO AVR 2015 convention brings jointly a neighborhood of researchers from academia and undefined, computing device scientists, engineers, and physicians so as to proportion issues of perspectives, wisdom, studies, and clinical and technical effects concerning state of the art strategies and applied sciences on digital and augmented fact purposes for medication, cultural background, schooling, business sectors, in addition to the demonstration of complex items and applied sciences.
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Information loss  checks the quantity of data that has been harmed during the protection process and therefore is no longer useful. Disclosure risk  measures the quantity of original data that can be discovered through the protected data. The remaining of this paper is structured as follows. In Section 2 we explain the methodology followed to go from a real social network like Twitter to obtaining a microdata dataset with explicit and implicit information about users. Section 3 contains the description of the protection method used in this work to protect the microdata dataset: the microaggregation.
2 User Profiles Generation The second step to do is to use the data structures collected by the crawler in order to get a profile for each user containing his location, his connected users and, his three most relevant topics of interest. In order to do this it should be noticed that information is not always explicitly given in the social networks. That is, using the Twitter API we can get the location but it is not possible to get the topics that a user is interested about because they are not specified nor described anywhere.
This lack of possible operations makes the protection a difficult task. Protection methods are typically evaluated using two measures: information loss and disclosure risk. Information loss  checks the quantity of data that has been harmed during the protection process and therefore is no longer useful. Disclosure risk  measures the quantity of original data that can be discovered through the protected data. The remaining of this paper is structured as follows. In Section 2 we explain the methodology followed to go from a real social network like Twitter to obtaining a microdata dataset with explicit and implicit information about users.