Multiple point of interest discovery and coverage with mobile wireless sensors

Environmental monitoring has become a typical application of wireless sensor networks. The concept of monitoring certain Points of Interest (PoIs) instead of the whole sensor field helps in reducing the costs of the deployment and improving the performance in terms of coverage. However, the problems of multiple PoI discovery, coverage and data report are still solved separately and there are no works that combine the aforementioned problems into a single deployment scheme. In this work, we present a novel approach for mobile sensor deployment, where we combine multiple PoI discovery and coverage with network connectivity preservation in order to capture the dynamics of the monitored area. Furthermore, we derive analytical expressions for circular movement parameters and examine the performance of our approach through extensive simulation campaigns.     

Arabic stop consonants characterisation and classification using the normalized energy in frequency bands

In general, speech is made with sequences of consonants (fricatives, nasals and stops), vowels and glides. The classification of the stop consonants remains one of the most challenging problems in speech recognition. In this paper, we propose a new approach based on the normalized energy in frequency bands in the release and closure phases in order to characterize and classify the Arabic stop consonants (/b/, /d/, /t/, /k/ and /q/) and to recognize the CV syllable. Classification experiments were performed using decision algorithms on stop consonants C and CV syllables extracted from an Arabic corpus. The results yielded to an overall stop consonants classification of 90.27% and syllables CV recognition upper than 90% for all stops.     

Energy bands and spectral cues for Arabic vowels recognition

The present study examines the short and long Arabic vowels (/a/, /a:/, /i/, /i:/, /u/ and /u:/) with a new approach based on three methods: formant frequencies extraction, spectral moments and energy bands. Among Arabic language characteristics compared to other languages are long vowels which can be pronounced with different duration length. The formant frequencies are the most exploited in characterizing vowels in different languages nevertheless using only formants was not very significant for vowels identification especially when production duration augments. Therefore, our approach is to broaden previous studies and present new tools in order to characterize long vowels compared to short ones.     

Increasing fairness and efficiency using the MadMac protocol in ad hoc networks

The IEEE 802.11 MAC layer is known for its unfairness behavior in ad hoc networks. Introducing fairness in the 802.11 MAC protocol may lead to a global throughput decrease. It is still a real challenge to design a fair MAC protocol for ad hoc networks that is distributed, topology independent, that relies on no explicit information exchanges and that is efficient, i.e. that achieves a good aggregate throughput. The MadMac protocol deals with fairness and throughput by maximizing aggregate throughput when unfairness is solved. Fairness provided by MadMac is only based on information provided by the 802.11 MAC layer. MadMac has been tested in many configurations that are known to be unfair and compared with three protocols (IEEE 802.11 and two fair MAC protocols). In these configurations, MadMac provides a good aggregate throughput while solving the fairness issues.