No abstract

The Internet of Things goes beyond the regular Internet by offering new functionalities and creating new range of services provided by the deployed objects. Therefore, one of the most challenging issues is to select the best service among similar functionally available ones. In this paper, we propose to involve both artifcial intelligence through the use of Artifcial Neural Network (ANN) and multi criteria analysis through the use of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) model in order to return the best service to the requestor. First, The ANN is introduced as a predictive model to estimate the Qualities of services (QoS) according to user context, service context and network context. Second, the TOPSIS model evaluates, then aggregates these QoS values in order to provide the best service according to user preferences. To improve the scalability of the proposed service selection system we conduct a parallel implementation of the prototype. General TermsService selection in the IoT

Bursaphelenchus tusciae is reported for the first time in Tunisia and North Africa, associated with the insect Hylurgus ligniperda Fabricius (Coleoptera: Curculionidae: Scolytinae). Nematode identification was based on restriction fragment length polymorphism analysis and sequencing of the internal transcribed spacer (ITS) regions of ribosomal DNA. Phylogenetic analysis revealed that Tunisian B. tusciae clusters together with two other B. tusciae isolates forming a separate group close to B. hildegardae and B. eggersi. As H. ligniperda is among maritime pine scolytids pests in Tunisia and is widely distributed in North Africa, this study is an important contribution to the knowledge of Bursaphelenchus species associated with bark beetles of pine forests in Tunisia and North Africa.

The pine wilt disease, caused by the pine wood nematode (PWN) Bursaphelenchus xylophilus, was detected in Europe in 1999 in Portugal and the longhorn beetle Monochamus galloprovincialis reported as the only vector since 2001. Although not present in northern Africa, it is feared that the PWN may cause significant damage if introduced into the Maghreb region, where several susceptible pine species which can serve as hosts are found, along with insects of the Monochamus genus which can act as vectors. In order to assess the risk of propagation of the wilt disease, we surveyed for the presence of possible vectors of the Monochamus genus in Tunisia, characterizing the distribution and emergence pattern. Studies were carried in nine locations with Aleppo pine (Pinus halepensis) forests. Sampling for insects was based on the trap tree technique, allowing beetles to lay eggs in the field and subsequently emerging. We confirmed the presence of Monochamus beetles in Tunisia, with only one species detected, M. galloprovincialis, which was widespread in the Aleppo pine forests. Our results show that this specie can develop and emerge from the basal, median and the upper part of the Aleppo pines with similar success. The larval development took nearly one year and adult emergences occurred from May to August during 2012. Results are discussed in view of similar biological studies conducted in other Mediterranean countries and the implications for the risk assessment of pine wilt disease in Tunisia.